{"slug":"kennethkhoocy-annotator-input-parity-check","name":"annotator-input-parity-check","description":"Before designing, training, or auditing ANY model that replicates\nhuman-annotated labels, audit the annotation protocol's INPUT — the exact\ndocument/evidence the human labelers consulted — and give the model that\nsame input. Use when: (1) designing a classifier/LLM extractor whose target\nis a hand-coded label set, (2) a label-replication model shows low recall\nconcentrated in a label subset and the diagnosis on offer is \"the label's\ninformation is not in the features\", (3) reviewers propose construct splits\n(e.g. \"designation vs record-evident\"), adjudication sittings, or per-domain\nstop rules to explain residual disagreement with gold, (4) validating an\nextraction pipeline against labels transcribed from a source document.\nSymptom of the underlying failure: elaborate theory accumulates to explain\nwhy gold is \"partially unpredictable\" when the model was simply never shown\nthe document the annotators read.","long_description":"---\nname: annotator-input-parity-check\ndescription: |\n  Before designing, training, or auditing ANY model that replicates\n  human-annotated labels, audit the annotation protocol's INPUT — the exact\n  document/evidence the human labelers consulted — and give the model that\n  same input. Use when: (1) designing a classifier/LLM extractor whose target\n  is a hand-coded label set, (2) a label-replication model shows low recall\n  concentrated in a label subset and the diagnosis on offer is \"the label's\n  information is not in the features\", (3) reviewers propose construct splits\n  (e.g. \"designation vs record-evident\"), adjudication sittings, or per-domain\n  stop rules to explain residual disagreement with gold, (4) validating an\n  extraction pipeline against labels transcribed from a source document.\n  Symptom of the underlying failure: elaborate theory accumulates to explain\n  why gold is \"partially unpredictable\" when the model was simply never shown\n  the document the annotators read.\nauthor: Claude Code\nversion: 1.0.0\ndate: 2026-07-21\n---\n\n# Annotator Input Parity Check\n\n## Problem\n\nA model built to replicate human labels is fed a different evidence base than\nthe one the annotators used. The mismatch masquerades as a modeling or\nconstruct problem: recall collapses on the label subset whose evidence lives\nonly in the annotators' source, audits produce increasingly sophisticated\ntheory (\"invisible\" positives, construct splits, per-domain reliability\ngates), and successive model generations inherit the wrong input because each\nreview critiques the lineage from inside the frozen input assumption.\n\n## Context / Trigger Conditions\n\n- Starting any label-replication build (classifier, LLM scorer, extractor)\n  against hand-coded gold.\n- A validation report says some share of gold positives have \"zero signal\" in\n  the model's input.\n- Proposals appear for: construct splits (what the model CAN see vs what the\n  label encodes), human adjudication of \"contested\" cells, stop rules\n  excluding weak domains, or accepting a permanent accuracy ceiling.\n- Verified instance (Specialist Directors US, 2026-07-21): three classifier\n  generations (bio-BERT AUC 0.5 → structured RoBERTa \"unclassifiable\" on 3/5\n  domains → LLM dossier scorer with E/D construct split + PI adjudication +\n  per-domain stop rules) all read director bios + BoardEx records, while the\n  RA labels were pure transcriptions of PROXY-STATEMENT disclosures (skills\n  matrices + bios, no exogenous data — confirmed in the source paper's\n  methodology, 41 Yale J. Reg. 652, 669-72). The \"invisible specialist\" mass\n  (43-79% of some domains) was simply the skills-matrix checkbox content the\n  models were never shown. Years of downstream apparatus dissolved once the\n  question \"what did the labelers actually read?\" was asked.\n\n## Solution\n\n1. Before any design work, write down the annotation protocol as the\n   annotators executed it: source document(s), what they could see, what they\n   could not, whether any exogenous data entered. Get this from the\n   codebook/paper methodology section, not from folklore. If the protocol is\n   unwritten, ask the PI directly: \"did labelers consult anything beyond X?\"\n2. Compare against the model's planned input. Any evidence the annotators had\n   that the model lacks is a hard recall ceiling on exactly the labels that\n   evidence determines — no architecture, prompt, or training fixes it.\n3. If a mismatch exists, prefer restoring input parity (give the model the\n   annotators' document) over modeling around the gap. For transcription-style\n   protocols, the task then becomes extraction, not prediction, and validation\n   against the hand labels becomes construct-matched (agreement should be\n   high; disagreement means extraction bugs, not construct philosophy).\n4. Only if input parity is impossible (annotators used private knowledge,\n   interviews, paywalled data) is a construct split the honest design — and\n   then the model's output must be named as a DIFFERENT variable, never\n   graded raw against the full gold.\n5. When auditing an EXISTING lineage: ask the parity question first, before\n   critiquing rubrics, thresholds, or gold quality. An audit that inherits the\n   input assumption can be internally excellent and still miss the dominant\n   error term.\n\n## Verification\n\n- The protocol-input inventory exists in writing and the model input is a\n  superset of it → recall ceilings from \"invisible\" labels should disappear;\n  residual disagreement decomposes into extraction errors (fixable) rather\n  than unknowable-label mass.\n- Quick falsification test for a claimed \"unpredictable\" label subset: pull 5\n  such gold positives, open the annotators' source document for each, and\n  check whether the label is visible there. If yes, the problem is input,\n  not construct.\n\n## Notes\n\n- Distinct from [llm-gold-bound-failure-check], which diagnoses gold that\n  fails to SEPARATE classes for a proposed revision; this skill diagnoses\n  model INPUT that omits the annotators' evidence. Run this parity check\n  first — gold-bound analysis of a parity-broken system wastes effort.\n- The mismatch is self-perpetuating across model generations: each successor\n  inherits the predecessor's feature pipeline, and each audit optimizes\n  within it. Breaking the frame requires asking about the ANNOTATORS, not\n  the model.\n- Construct splits built on a parity-broken system may still have salvage\n  value for a different question (e.g. record-evident-but-undisclosed\n  expertise is analytically interesting in its own right) — reframe, don't\n  necessarily discard.\n","tagline":"Before designing, training, or auditing ANY model that replicates\nhuman-annotated labels, audit the annotation protocol's INPUT — the exact\ndocument/evidence the human labelers consulted — and give the model that\nsame input. Use when: (1) designing a classifier/LLM extractor whos","category":"security","tags":["agent-skill"],"author":"Claude Code","verified":false,"attribution":{"status":"registry_indexed","statusLabel":"Registry indexed","shortLabel":"REGISTRY INDEXED","sourceLabel":"recursive skill source sync","sourceDetail":"kennethkhoocy/applied-micro-skills","creatorName":"Claude Code","creatorUrl":"https://github.com/kennethkhoocy","sourceUrl":"https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/kennethkhoocy-annotator-input-parity-check#claim-this-skill","claimCta":"Claim this skill","trustNote":"This listing was indexed from public sources and is not marked official until a maintainer claim is approved.","publicNote":"Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals."},"stats":{"stars":47,"forks":0,"verified_installs":0,"successful_runs":0,"total_outcomes":0,"rating":0,"review_count":0,"quality_score":35.47},"quality":{"score":64,"tier":"promising","label":"Promising","summary":"Useful candidate, but compare it with alternatives before adopting.","signals":[{"label":"GitHub stars","value":"47","tone":"neutral"},{"label":"Freshness","value":"Today","tone":"positive"},{"label":"Install ready","value":"Yes","tone":"positive"},{"label":"License","value":"MIT","tone":"neutral"}],"warnings":["Low GitHub adoption signal","No explicit 'Limitations' section, though the Notes section partially covers boundaries."]},"trust":{"version":"trust-score-v5","score":63,"base_score":71,"outcome_confidence":0,"tier":"review","label":"Sandbox only","summary":"Useful candidate with missing or mixed trust signals. 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issue activity unavailable in current metadata"]},"outcomeEvidence":{"total":0,"successes":0,"failures":0,"notRelevant":0,"successRate":null,"installAttempts":0,"riskBlocked":0,"setupRequired":0,"installSuccessRate":null,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"recentSuccessRate":null,"recentFailureRate":null,"uniqueAgents":0,"agentProvenScore":0,"agentProvenLabel":"Needs first agent run","lastOutcomeAt":null,"label":"No agent outcome data yet"},"autoInstall":{"allowed":false,"sandboxRequired":true,"policy":"human_review_before_install","reason":"Compare alternatives before installing."},"outcome_loop":{"version":"openagentskill-agent-outcome-v3","required_after_install":true,"endpoint":"/api/agent/outcome","method":"POST","event_id_source":"feedback.event_id, install_receipt.resolve_event_id, or decision_packet.outcome_feedback.event_id","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"required_fields":["event_id","skill_slug","task"],"quality_fields":["task_success","output_quality","error_type","human_review_required","used_in_production","workspace","evidence_url","time_to_useful_ms"],"ranking_inputs_updated":["Trust Score v5 outcome confidence","Agent Proven Score","Resolve ranking task-fit evidence","Skill detail machine-readable metadata","Outcome leaderboard"]},"agent_contract":{"suited_tasks":["security","agent-skill"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI"],"install_command":"npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check","trust_score":63,"trust_version":"trust-score-v5","risk_level":"medium","do_not_use_when":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace"],"before_install":["Read the audit page and machine-readable metadata.","Confirm the install command, license, and permission surface fit the workspace.","Get explicit human approval or choose an alternative before installing."],"after_run":["Report the outcome to /api/agent/outcome using the resolve event id.","Include output_quality, workspace, human_review_required, and evidence_url when available.","Re-resolve before broad production rollout."]},"bestFor":["security","agent-skill"],"doNotUseFor":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace"],"knownRisks":["No explicit 'Limitations' section, though the Notes section partially covers boundaries.","Low GitHub adoption signal","Quality score needs review","GitHub adoption: 47 GitHub stars","Stars/forks activity: 47 stars, 0 forks; issue activity unavailable in current metadata"],"backward_compatible":{"trust_score_v4":{"version":"trust-score-v4","score":71,"tier":"review","label":"Manual review","summary":"Potentially useful, but at least one trust signal needs human inspection."}}},"trust_score_v4":{"version":"trust-score-v4","score":71,"tier":"review","label":"Manual review","summary":"Potentially useful, but at least one trust signal needs human inspection.","recommendedAction":"Inspect the repository, license, and recent activity before connecting it to agent workflows.","dimensions":[{"id":"github_adoption","label":"GitHub adoption","score":48,"weight":0.13,"status":"warn","detail":"47 GitHub stars"},{"id":"repo_activity","label":"Stars/forks activity","score":43,"weight":0.08,"status":"warn","detail":"47 stars, 0 forks; issue activity unavailable in current metadata"},{"id":"maintenance","label":"Recent maintenance","score":100,"weight":0.14,"status":"pass","detail":"Pushed today"},{"id":"license","label":"License clarity","score":86,"weight":0.09,"status":"pass","detail":"MIT"},{"id":"documentation","label":"README/SKILL.md completeness","score":76,"weight":0.14,"status":"info","detail":"Public metadata needs stronger README/SKILL.md context"},{"id":"dependency_risk","label":"Dependency/runtime risk","score":90,"weight":0.12,"status":"pass","detail":"no major dependency risk hints in public metadata"},{"id":"installability","label":"Install availability","score":92,"weight":0.1,"status":"pass","detail":"npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check"},{"id":"install_safety","label":"Install command safety","score":92,"weight":0.1,"status":"pass","detail":"standard package or runtime install path"},{"id":"permission_surface","label":"Permission surface","score":86,"weight":0.07,"status":"pass","detail":"filesystem or document access"},{"id":"repository","label":"Repository evidence","score":86,"weight":0.04,"status":"pass","detail":"https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check"},{"id":"review_status","label":"Review status","score":66,"weight":0.05,"status":"info","detail":"AI review data available"},{"id":"agent_outcomes","label":"Agent Proven outcomes","score":54,"weight":0.13,"status":"info","detail":"No agent outcome data yet"}],"checks":[{"status":"warn","label":"GitHub adoption","detail":"47 GitHub stars"},{"status":"warn","label":"Stars/forks activity","detail":"47 stars, 0 forks; issue activity unavailable in current metadata"},{"status":"pass","label":"Recent maintenance","detail":"Pushed today"},{"status":"pass","label":"License clarity","detail":"MIT"},{"status":"info","label":"README/SKILL.md completeness","detail":"Public metadata needs stronger README/SKILL.md context"},{"status":"pass","label":"Dependency/runtime risk","detail":"no major dependency risk hints in public metadata"},{"status":"pass","label":"Install availability","detail":"npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check"},{"status":"pass","label":"Install command safety","detail":"standard package or runtime install path"},{"status":"pass","label":"Permission surface","detail":"filesystem or document access"},{"status":"pass","label":"Repository evidence","detail":"https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check"},{"status":"info","label":"Review status","detail":"AI review data available"},{"status":"info","label":"Agent Proven outcomes","detail":"No agent outcome data yet"},{"status":"warn","label":"Ownership","detail":"No approved owner claim yet"},{"status":"info","label":"OpenAgentSkill usage","detail":"No local usage activity yet"},{"status":"info","label":"Agent outcomes","detail":"No agent outcome data yet"}],"strengths":["AI review approved","Install path is available","Repository evidence is available","Recently maintained repository","Install command has no obvious high-risk pattern"],"warnings":["No explicit 'Limitations' section, though the Notes section partially covers boundaries.","Low GitHub adoption signal","Quality score needs review","GitHub adoption: 47 GitHub stars","Stars/forks activity: 47 stars, 0 forks; issue activity unavailable in current metadata"],"evidence":{"stars":"47 GitHub stars","repoActivity":"47 stars, 0 forks","lastPushed":"Pushed today","license":"MIT","repository":"https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check","install":"npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check","installSafety":"standard package or runtime install path","permissionSurface":"filesystem or document access","documentation":"Usable metadata, review docs","agentOutcomes":"No agent outcome data yet"},"installReadiness":{"ready":true,"command":"npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check","policy":"human_review_before_install","label":"Human review before install","notes":["Install path is available","Repository evidence is available","License is declared","No Agent Proven outcome evidence yet","Pushed today"]},"agentCompatibility":["Codex","Claude Code","Cursor","OpenAgentSkill CLI"],"riskSummary":{"level":"medium","label":"Review before production","notes":["No explicit 'Limitations' section, though the Notes section partially covers boundaries.","Low GitHub adoption signal","Quality score needs review","GitHub adoption: 47 GitHub stars","Stars/forks activity: 47 stars, 0 forks; issue activity unavailable in current metadata"]},"outcomeEvidence":{"total":0,"successes":0,"failures":0,"notRelevant":0,"successRate":null,"installAttempts":0,"riskBlocked":0,"setupRequired":0,"installSuccessRate":null,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"recentSuccessRate":null,"recentFailureRate":null,"uniqueAgents":0,"agentProvenScore":0,"agentProvenLabel":"Needs first agent run","lastOutcomeAt":null,"label":"No agent outcome data yet"},"autoInstall":{"allowed":false,"sandboxRequired":true,"policy":"human_review_before_install","reason":"Human review or sandbox validation is required before automatic installation."},"bestFor":["security","agent-skill"],"doNotUseFor":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace"],"knownRisks":["No explicit 'Limitations' section, though the Notes section partially covers boundaries.","Low GitHub adoption signal","Quality score needs review","GitHub adoption: 47 GitHub stars","Stars/forks activity: 47 stars, 0 forks; issue activity unavailable in current metadata"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"outcome_stats":null,"safety":{"score":61,"level":"review_before_install","label":"Review before install","safety_tier":{"tier":"reviewed","label":"Reviewed with permission notes","badge":"REVIEWED","summary":"Usable candidate, but the agent should surface permission and audit notes before installation.","recommended_action":"Require human approval before installing into a real workspace.","auto_install_policy":"review","reasons":["No explicit 'Limitations' section, though the Notes section partially covers boundaries.","61/100 agent safety score"]},"auto_install_allowed":false,"human_review_required":true,"blocked":false,"audit_risk":"needs_review","permission_hints":[{"id":"network","label":"Network access","reason":"Skill likely fetches remote pages, APIs, repositories, or external services.","severity":"medium"},{"id":"filesystem","label":"Filesystem access","reason":"Skill may read or write project files, documents, generated artifacts, or local workspace state.","severity":"medium"}],"policy_warnings":["No explicit 'Limitations' section, though the Notes section partially covers boundaries."],"constraints_applied":{"max_risk":"medium","needs_install_command":true,"min_stars":0}},"safety_gate":{"tier":"reviewed","label":"Reviewed with permission notes","badge":"REVIEWED","auto_install_policy":"review","auto_install_allowed":false,"blocked":false,"human_review_required":true,"recommended_action":"Require human approval before installing into a real workspace.","reasons":["No explicit 'Limitations' section, though the Notes section partially covers boundaries.","61/100 agent safety score"]},"eval":{"version":"openagentskill-skill-eval-v1","status":"review","score":70,"risk_level":"medium","decision":{"recommendation":"manual_review","reason":"Require human approval before installing into a real workspace.","auto_install_allowed":false,"policy":"review","human_review_required":true},"blockers":[],"warnings":["Trust score: Potentially useful, but at least one trust signal needs human inspection.","Audit score: Needs review","Agent safety gate: Usable candidate, but the agent should surface permission and audit notes before installation.","README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context","No explicit 'Limitations' section, though the Notes section partially covers boundaries.","The skill description is long but well-structured; could be slightly more concise for quick scanning.","Low GitHub adoption signal","Quality score needs review","GitHub adoption: 47 GitHub stars","Stars/forks activity: 47 stars, 0 forks; issue activity unavailable in current metadata"],"validation_plan":["Inspect repository, README/SKILL.md, license, and recent commits before production use.","Install in an isolated workspace or sandbox with no production secrets available.","Run the smallest representative task and record files touched, commands run, network access, and outputs.","Compare the selected skill against at least one alternative when the eval status is review or failed.","Promote only after the agent reports a successful verification result and unresolved warnings are accepted."],"checks":[{"id":"task_fit","label":"Task fit","status":"pass","score":84,"required_for_auto_install":true,"detail":"Task wording matches this skill metadata.","evidence":["Evaluate annotator-input-parity-check before installing it in an agent workflow","security","Research agents workflows; Claude Code teams; builders willing to evaluate younger projects"]},{"id":"install_path","label":"Install path","status":"pass","score":92,"required_for_auto_install":true,"detail":"Install handoff is available.","evidence":["npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check"]},{"id":"install_safety","label":"Install command safety","status":"pass","score":92,"required_for_auto_install":true,"detail":"standard package or runtime install path","evidence":["npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check"]},{"id":"trust_score","label":"Trust score","status":"warn","score":71,"required_for_auto_install":true,"detail":"Potentially useful, but at least one trust signal needs human inspection.","evidence":["Manual review","47 GitHub stars","MIT"]},{"id":"audit_score","label":"Audit score","status":"warn","score":77,"required_for_auto_install":true,"detail":"Needs review","evidence":["No explicit 'Limitations' section, though the Notes section partially covers boundaries."]},{"id":"agent_safety_gate","label":"Agent safety gate","status":"warn","score":61,"required_for_auto_install":true,"detail":"Usable candidate, but the agent should surface permission and audit notes before installation.","evidence":["Require human approval before installing into a real workspace.","No explicit 'Limitations' section, though the Notes section partially covers boundaries."]},{"id":"readme_skillmd_completeness","label":"README/SKILL.md completeness","status":"warn","score":76,"required_for_auto_install":false,"detail":"Public metadata needs stronger README/SKILL.md context","evidence":["Usable metadata, review docs"]},{"id":"license_clarity","label":"License clarity","status":"pass","score":86,"required_for_auto_install":true,"detail":"MIT","evidence":["MIT"]},{"id":"recent_maintenance","label":"Recent maintenance","status":"pass","score":100,"required_for_auto_install":false,"detail":"Pushed today","evidence":["Pushed today"]},{"id":"permission_surface","label":"Permission surface","status":"pass","score":86,"required_for_auto_install":true,"detail":"filesystem or document access","evidence":["Network access: medium","Filesystem access: medium"]},{"id":"alternatives","label":"Alternatives available","status":"info","score":55,"required_for_auto_install":false,"detail":"No close alternatives were found in the current shortlist.","evidence":[]}],"endpoints":{"web":"https://www.openagentskill.com/skills/kennethkhoocy-annotator-input-parity-check/evals","api":"/api/agent/evals?slug=kennethkhoocy-annotator-input-parity-check","text":"/api/agent/evals?slug=kennethkhoocy-annotator-input-parity-check&format=text"}},"agent_readable_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"kennethkhoocy-annotator-input-parity-check","name":"annotator-input-parity-check","description":"Before designing, training, or auditing ANY model that replicates\nhuman-annotated labels, audit the annotation protocol's INPUT — the exact\ndocument/evidence the human labelers consulted — and give the model that\nsame input. Use when: (1) designing a classifier/LLM extractor whose target\nis a hand-coded label set, (2) a label-replication model shows low recall\nconcentrated in a label subset and the diagnosis on offer is \"the label's\ninformation is not in the features\", (3) reviewers propose construct splits\n(e.g. \"designation vs record-evident\"), adjudication sittings, or per-domain\nstop rules to explain residual disagreement with gold, (4) validating an\nextraction pipeline against labels transcribed from a source document.\nSymptom of the underlying failure: elaborate theory accumulates to explain\nwhy gold is \"partially unpredictable\" when the model was simply never shown\nthe document the annotators read.","category":"security","url":"https://www.openagentskill.com/skills/kennethkhoocy-annotator-input-parity-check","repository":"https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check","github_repo":"kennethkhoocy/applied-micro-skills"},"suited_tasks":["Research agents workflows","Claude Code teams","builders willing to evaluate younger projects","Search sources","Extract claims","Synthesize findings","Navigate pages","Click and type safely"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install kennethkhoocy-annotator-input-parity-check"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"annotator-input-parity-check\" agent skill from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Before designing, training, or auditing ANY model that replicates human-annotated labels, audit the annotation protocol's INPUT — the exact document/evidence the human labelers consulted — and give the model that same input. Use when: (1) designing a classifier/LLM extractor whose target is a hand-coded label set, (2) a label-replication model shows low recall concentrated in a label subset and the diagnosis on offer is \"the label's information is not in the features\", (3) reviewers propose construct splits (e.g. \"designation vs record-evident\"), adjudication sittings, or per-domain stop rules to explain residual disagreement with gold, (4) validating an extraction pipeline against labels transcribed from a source document. Symptom of the underlying failure: elaborate theory accumulates to explain why gold is \"partially unpredictable\" when the model was simply never shown the document the annotators read. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"kennethkhoocy-annotator-input-parity-check\",\"task\":\"Install annotator-input-parity-check\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"annotator-input-parity-check\" as a Claude Code skill from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Before designing, training, or auditing ANY model that replicates human-annotated labels, audit the annotation protocol's INPUT — the exact document/evidence the human labelers consulted — and give the model that same input. Use when: (1) designing a classifier/LLM extractor whose target is a hand-coded label set, (2) a label-replication model shows low recall concentrated in a label subset and the diagnosis on offer is \"the label's information is not in the features\", (3) reviewers propose construct splits (e.g. \"designation vs record-evident\"), adjudication sittings, or per-domain stop rules to explain residual disagreement with gold, (4) validating an extraction pipeline against labels transcribed from a source document. Symptom of the underlying failure: elaborate theory accumulates to explain why gold is \"partially unpredictable\" when the model was simply never shown the document the annotators read. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"kennethkhoocy-annotator-input-parity-check\",\"task\":\"Install annotator-input-parity-check\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"annotator-input-parity-check\" from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Before designing, training, or auditing ANY model that replicates human-annotated labels, audit the annotation protocol's INPUT — the exact document/evidence the human labelers consulted — and give the model that same input. Use when: (1) designing a classifier/LLM extractor whose target is a hand-coded label set, (2) a label-replication model shows low recall concentrated in a label subset and the diagnosis on offer is \"the label's information is not in the features\", (3) reviewers propose construct splits (e.g. \"designation vs record-evident\"), adjudication sittings, or per-domain stop rules to explain residual disagreement with gold, (4) validating an extraction pipeline against labels transcribed from a source document. Symptom of the underlying failure: elaborate theory accumulates to explain why gold is \"partially unpredictable\" when the model was simply never shown the document the annotators read. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"kennethkhoocy-annotator-input-parity-check\",\"task\":\"Install annotator-input-parity-check\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/kennethkhoocy-annotator-input-parity-check/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/kennethkhoocy-annotator-input-parity-check"},"trust":{"score":71,"label":"Manual review","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"47 GitHub stars","repoActivity":"47 stars, 0 forks","lastPushed":"Pushed today","license":"MIT","repository":"https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check","install":"npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check","installSafety":"standard package or runtime install path","permissionSurface":"filesystem or document access","documentation":"Usable metadata, review docs","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["security","agent-skill"],"known_risks":["No explicit 'Limitations' section, though the Notes section partially covers boundaries.","Low GitHub adoption signal","Quality score needs review","GitHub adoption: 47 GitHub stars","Stars/forks activity: 47 stars, 0 forks; issue activity unavailable in current metadata"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":77,"risk_level":"needs_review","risk_label":"Needs review","warnings":["No explicit 'Limitations' section, though the Notes section partially covers boundaries.","The skill description is long but well-structured; could be slightly more concise for quick scanning.","Low GitHub adoption signal","Quality score needs review","GitHub adoption: 47 GitHub stars","Stars/forks activity: 47 stars, 0 forks; issue activity unavailable in current metadata"]},"safety_gate":{"tier":"reviewed","label":"Reviewed with permission notes","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Require human approval before installing into a real workspace."},"quality":{"score":64,"label":"Promising"},"supply":{"track":"Research and knowledge work","scenario":"Research agents","maintenance":"Pushed today","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","production agents without a repository review","Low GitHub adoption signal","No explicit 'Limitations' section, though the Notes section partially covers boundaries.","No OpenAgentSkill engagement data yet","The skill description is long but well-structured; could be slightly more concise for quick scanning.","Quality score needs review","GitHub adoption: 47 GitHub stars"],"agent_contract":{"task_input":"Use annotator-input-parity-check in an agent workflow","recommended_action":"Require human approval before installing into a real workspace.","install_policy":"review","minimum_review_before_use":["Trust: 71/100 Manual review","Audit: 77/100 Needs review","Safety: 61/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"kennethkhoocy-annotator-input-parity-check (annotator-input-parity-check)","install_command":"npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check","risk_summary":"Needs review; Reviewed with permission notes; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"kennethkhoocy-annotator-input-parity-check","task":"Use annotator-input-parity-check in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/kennethkhoocy-annotator-input-parity-check","api":"https://www.openagentskill.com/api/agent/skills/kennethkhoocy-annotator-input-parity-check","audit":"https://www.openagentskill.com/skills/kennethkhoocy-annotator-input-parity-check/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=kennethkhoocy-annotator-input-parity-check&task=Use%20annotator-input-parity-check%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20annotator-input-parity-check%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20annotator-input-parity-check%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/kennethkhoocy-annotator-input-parity-check/install","manifest":"https://www.openagentskill.com/api/registry/manifest/kennethkhoocy-annotator-input-parity-check"}},"machine_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"kennethkhoocy-annotator-input-parity-check","name":"annotator-input-parity-check","description":"Before designing, training, or auditing ANY model that replicates\nhuman-annotated labels, audit the annotation protocol's INPUT — the exact\ndocument/evidence the human labelers consulted — and give the model that\nsame input. Use when: (1) designing a classifier/LLM extractor whose target\nis a hand-coded label set, (2) a label-replication model shows low recall\nconcentrated in a label subset and the diagnosis on offer is \"the label's\ninformation is not in the features\", (3) reviewers propose construct splits\n(e.g. \"designation vs record-evident\"), adjudication sittings, or per-domain\nstop rules to explain residual disagreement with gold, (4) validating an\nextraction pipeline against labels transcribed from a source document.\nSymptom of the underlying failure: elaborate theory accumulates to explain\nwhy gold is \"partially unpredictable\" when the model was simply never shown\nthe document the annotators read.","category":"security","url":"https://www.openagentskill.com/skills/kennethkhoocy-annotator-input-parity-check","repository":"https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check","github_repo":"kennethkhoocy/applied-micro-skills"},"suited_tasks":["Research agents workflows","Claude Code teams","builders willing to evaluate younger projects","Search sources","Extract claims","Synthesize findings","Navigate pages","Click and type safely"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install kennethkhoocy-annotator-input-parity-check"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"annotator-input-parity-check\" agent skill from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Before designing, training, or auditing ANY model that replicates human-annotated labels, audit the annotation protocol's INPUT — the exact document/evidence the human labelers consulted — and give the model that same input. Use when: (1) designing a classifier/LLM extractor whose target is a hand-coded label set, (2) a label-replication model shows low recall concentrated in a label subset and the diagnosis on offer is \"the label's information is not in the features\", (3) reviewers propose construct splits (e.g. \"designation vs record-evident\"), adjudication sittings, or per-domain stop rules to explain residual disagreement with gold, (4) validating an extraction pipeline against labels transcribed from a source document. Symptom of the underlying failure: elaborate theory accumulates to explain why gold is \"partially unpredictable\" when the model was simply never shown the document the annotators read. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"kennethkhoocy-annotator-input-parity-check\",\"task\":\"Install annotator-input-parity-check\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"annotator-input-parity-check\" as a Claude Code skill from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Before designing, training, or auditing ANY model that replicates human-annotated labels, audit the annotation protocol's INPUT — the exact document/evidence the human labelers consulted — and give the model that same input. Use when: (1) designing a classifier/LLM extractor whose target is a hand-coded label set, (2) a label-replication model shows low recall concentrated in a label subset and the diagnosis on offer is \"the label's information is not in the features\", (3) reviewers propose construct splits (e.g. \"designation vs record-evident\"), adjudication sittings, or per-domain stop rules to explain residual disagreement with gold, (4) validating an extraction pipeline against labels transcribed from a source document. Symptom of the underlying failure: elaborate theory accumulates to explain why gold is \"partially unpredictable\" when the model was simply never shown the document the annotators read. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"kennethkhoocy-annotator-input-parity-check\",\"task\":\"Install annotator-input-parity-check\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"annotator-input-parity-check\" from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Before designing, training, or auditing ANY model that replicates human-annotated labels, audit the annotation protocol's INPUT — the exact document/evidence the human labelers consulted — and give the model that same input. Use when: (1) designing a classifier/LLM extractor whose target is a hand-coded label set, (2) a label-replication model shows low recall concentrated in a label subset and the diagnosis on offer is \"the label's information is not in the features\", (3) reviewers propose construct splits (e.g. \"designation vs record-evident\"), adjudication sittings, or per-domain stop rules to explain residual disagreement with gold, (4) validating an extraction pipeline against labels transcribed from a source document. Symptom of the underlying failure: elaborate theory accumulates to explain why gold is \"partially unpredictable\" when the model was simply never shown the document the annotators read. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"kennethkhoocy-annotator-input-parity-check\",\"task\":\"Install annotator-input-parity-check\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/kennethkhoocy-annotator-input-parity-check/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/kennethkhoocy-annotator-input-parity-check"},"trust":{"score":71,"label":"Manual review","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"47 GitHub stars","repoActivity":"47 stars, 0 forks","lastPushed":"Pushed today","license":"MIT","repository":"https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check","install":"npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check","installSafety":"standard package or runtime install path","permissionSurface":"filesystem or document access","documentation":"Usable metadata, review docs","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["security","agent-skill"],"known_risks":["No explicit 'Limitations' section, though the Notes section partially covers boundaries.","Low GitHub adoption signal","Quality score needs review","GitHub adoption: 47 GitHub stars","Stars/forks activity: 47 stars, 0 forks; issue activity unavailable in current metadata"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":77,"risk_level":"needs_review","risk_label":"Needs review","warnings":["No explicit 'Limitations' section, though the Notes section partially covers boundaries.","The skill description is long but well-structured; could be slightly more concise for quick scanning.","Low GitHub adoption signal","Quality score needs review","GitHub adoption: 47 GitHub stars","Stars/forks activity: 47 stars, 0 forks; issue activity unavailable in current metadata"]},"safety_gate":{"tier":"reviewed","label":"Reviewed with permission notes","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Require human approval before installing into a real workspace."},"quality":{"score":64,"label":"Promising"},"supply":{"track":"Research and knowledge work","scenario":"Research agents","maintenance":"Pushed today","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","production agents without a repository review","Low GitHub adoption signal","No explicit 'Limitations' section, though the Notes section partially covers boundaries.","No OpenAgentSkill engagement data yet","The skill description is long but well-structured; could be slightly more concise for quick scanning.","Quality score needs review","GitHub adoption: 47 GitHub stars"],"agent_contract":{"task_input":"Use annotator-input-parity-check in an agent workflow","recommended_action":"Require human approval before installing into a real workspace.","install_policy":"review","minimum_review_before_use":["Trust: 71/100 Manual review","Audit: 77/100 Needs review","Safety: 61/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"kennethkhoocy-annotator-input-parity-check (annotator-input-parity-check)","install_command":"npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check","risk_summary":"Needs review; Reviewed with permission notes; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"kennethkhoocy-annotator-input-parity-check","task":"Use annotator-input-parity-check in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/kennethkhoocy-annotator-input-parity-check","api":"https://www.openagentskill.com/api/agent/skills/kennethkhoocy-annotator-input-parity-check","audit":"https://www.openagentskill.com/skills/kennethkhoocy-annotator-input-parity-check/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=kennethkhoocy-annotator-input-parity-check&task=Use%20annotator-input-parity-check%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20annotator-input-parity-check%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20annotator-input-parity-check%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/kennethkhoocy-annotator-input-parity-check/install","manifest":"https://www.openagentskill.com/api/registry/manifest/kennethkhoocy-annotator-input-parity-check"}},"supply_profile":{"track":{"slug":"research","label":"Research and knowledge work","shortLabel":"Research","description":"Deep research, source comparison, literature review, RAG, knowledge search, and reports."},"scenario":{"label":"Research agents","description":"I need my agent to research a topic, compare sources, and produce a concise report.","useCases":[{"slug":"research-agents","title":"Research agents"},{"slug":"browser-automation","title":"Browser automation"},{"slug":"document-processing","title":"Document processing"}]},"applicableAgents":["Claude Code","CLI","Codex","Cursor"],"install":{"ready":true,"command":"npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check","primaryTarget":"CLI","targetCount":4},"githubQuality":{"stars":47,"starsLabel":"47","forks":0,"license":"MIT","qualityScore":64,"trustScore":71,"auditScore":77},"maintenance":{"status":"fresh","label":"Pushed today","daysSincePush":0,"lastPushedAt":"2026-08-24T03:17:05+00:00"},"risk":{"level":"needs_review","label":"Needs review","requiresReview":true,"notes":["No explicit 'Limitations' section, though the Notes section partially covers boundaries.","The skill description is long but well-structured; could be slightly more concise for quick scanning.","Low GitHub adoption signal","Quality score needs review","GitHub adoption: 47 GitHub stars"]},"coverageTags":["Research","Research agents","security","agent-skill"]},"audit":{"audit_score":77,"risk_level":"needs_review","risk_label":"Needs review","quality_score":64,"trust_score":71,"maintenance_score":100,"security_score":80,"install_score":92,"warnings":["No explicit 'Limitations' section, though the Notes section partially covers boundaries.","The skill description is long but well-structured; could be slightly more concise for quick scanning.","Low GitHub adoption signal","Quality score needs review","GitHub adoption: 47 GitHub stars","Stars/forks activity: 47 stars, 0 forks; issue activity unavailable in current metadata"]},"quality_signals":{"model":"v2","star_score":11.77,"usage_score":0,"review_score":5.7,"metadata_score":3,"freshness_score":15},"platforms":["Claude Code"],"use_cases":[{"slug":"research-agents","title":"Research agents","url":"https://www.openagentskill.com/use-cases/research-agents"},{"slug":"browser-automation","title":"Browser automation","url":"https://www.openagentskill.com/use-cases/browser-automation"},{"slug":"document-processing","title":"Document processing","url":"https://www.openagentskill.com/use-cases/document-processing"},{"slug":"testing-qa","title":"Testing and QA","url":"https://www.openagentskill.com/use-cases/testing-qa"}],"stacks":[{"slug":"research-report-agent","title":"Research report agent","url":"https://www.openagentskill.com/collections/research-report-agent"},{"slug":"browser-qa-agent","title":"Browser QA agent","url":"https://www.openagentskill.com/collections/browser-qa-agent"},{"slug":"coding-review-agent","title":"Coding review agent","url":"https://www.openagentskill.com/collections/coding-review-agent"}],"install":"npx skills add kennethkhoocy/applied-micro-skills --skill annotator-input-parity-check","install_targets":[{"id":"openagentskill-cli","label":"CLI","title":"OpenAgentSkill CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install kennethkhoocy-annotator-input-parity-check","description":"Resolve policy, run the source installer safely, and report a verified install receipt.","copyLabel":"Copy command"},{"id":"codex","label":"Codex","title":"Codex install prompt","kind":"agent-prompt","value":"Install the \"annotator-input-parity-check\" agent skill from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Before designing, training, or auditing ANY model that replicates human-annotated labels, audit the annotation protocol's INPUT — the exact document/evidence the human labelers consulted — and give the model that same input. Use when: (1) designing a classifier/LLM extractor whose target is a hand-coded label set, (2) a label-replication model shows low recall concentrated in a label subset and the diagnosis on offer is \"the label's information is not in the features\", (3) reviewers propose construct splits (e.g. \"designation vs record-evident\"), adjudication sittings, or per-domain stop rules to explain residual disagreement with gold, (4) validating an extraction pipeline against labels transcribed from a source document. Symptom of the underlying failure: elaborate theory accumulates to explain why gold is \"partially unpredictable\" when the model was simply never shown the document the annotators read. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"kennethkhoocy-annotator-input-parity-check\",\"task\":\"Install annotator-input-parity-check\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Give Codex a repo-aware install prompt when the skill is not available through a local CLI.","copyLabel":"Copy prompt"},{"id":"claude-code","label":"Claude Code","title":"Claude Code skill prompt","kind":"agent-prompt","value":"Add \"annotator-input-parity-check\" as a Claude Code skill from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Before designing, training, or auditing ANY model that replicates human-annotated labels, audit the annotation protocol's INPUT — the exact document/evidence the human labelers consulted — and give the model that same input. Use when: (1) designing a classifier/LLM extractor whose target is a hand-coded label set, (2) a label-replication model shows low recall concentrated in a label subset and the diagnosis on offer is \"the label's information is not in the features\", (3) reviewers propose construct splits (e.g. \"designation vs record-evident\"), adjudication sittings, or per-domain stop rules to explain residual disagreement with gold, (4) validating an extraction pipeline against labels transcribed from a source document. Symptom of the underlying failure: elaborate theory accumulates to explain why gold is \"partially unpredictable\" when the model was simply never shown the document the annotators read. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"kennethkhoocy-annotator-input-parity-check\",\"task\":\"Install annotator-input-parity-check\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this prompt to ask Claude Code to add the skill and explain the local activation steps.","copyLabel":"Copy prompt"},{"id":"cursor","label":"Cursor","title":"Cursor rule prompt","kind":"agent-prompt","value":"Turn \"annotator-input-parity-check\" from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Before designing, training, or auditing ANY model that replicates human-annotated labels, audit the annotation protocol's INPUT — the exact document/evidence the human labelers consulted — and give the model that same input. Use when: (1) designing a classifier/LLM extractor whose target is a hand-coded label set, (2) a label-replication model shows low recall concentrated in a label subset and the diagnosis on offer is \"the label's information is not in the features\", (3) reviewers propose construct splits (e.g. \"designation vs record-evident\"), adjudication sittings, or per-domain stop rules to explain residual disagreement with gold, (4) validating an extraction pipeline against labels transcribed from a source document. Symptom of the underlying failure: elaborate theory accumulates to explain why gold is \"partially unpredictable\" when the model was simply never shown the document the annotators read. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"kennethkhoocy-annotator-input-parity-check\",\"task\":\"Install annotator-input-parity-check\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this when installing as Cursor project rules or reusable agent instructions.","copyLabel":"Copy prompt"}],"repository":"https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check","github_repo":"kennethkhoocy/applied-micro-skills","version":"1.0.0","license":"MIT","urls":{"web":"https://www.openagentskill.com/skills/kennethkhoocy-annotator-input-parity-check","repository":"https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/annotator-input-parity-check","api":"/api/agent/skills/kennethkhoocy-annotator-input-parity-check","install_api":"/api/skills/kennethkhoocy-annotator-input-parity-check/install"},"meta":{"created_at":"2026-08-24T04:36:40.883453+00:00","updated_at":"2026-08-24T06:36:18.925943+00:00","agent_friendly":true}}