{"slug":"kennethkhoocy-pyfixest-grid-sharding","name":"pyfixest-grid-sharding","description":"Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run\nsequentially) that stay slow despite demeaner_backend=\"cupy64\" and an idle\nGPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row\npanel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and\nnvidia-smi shows ~0% GPU utilization with a resident cupy context, (3)\nplanning any worker prompt that will run a model grid (robustness variants x\nFE structures x domains). Root cause: per-model CPU-side single-threaded\nfixed costs (formulaic model-matrix build, interaction construction,\nsingleton detection, cluster vcov) dominate wall time; GPU demeaning is a\nsmall slice. Fix: shard the model grid across OS processes and/or use\npyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT.","long_description":"---\nname: pyfixest-grid-sharding\ndescription: |\n  Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run\n  sequentially) that stay slow despite demeaner_backend=\"cupy64\" and an idle\n  GPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row\n  panel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and\n  nvidia-smi shows ~0% GPU utilization with a resident cupy context, (3)\n  planning any worker prompt that will run a model grid (robustness variants x\n  FE structures x domains). Root cause: per-model CPU-side single-threaded\n  fixed costs (formulaic model-matrix build, interaction construction,\n  singleton detection, cluster vcov) dominate wall time; GPU demeaning is a\n  small slice. Fix: shard the model grid across OS processes and/or use\n  pyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT.\nauthor: Claude Code\nversion: 1.0.0\ndate: 2026-07-21\n---\n\n# pyfixest Grid Sharding\n\n## Problem\n\nA regression grid (e.g. 2 measures x 3 FE structures x pooled+per-domain x 3\nlabel variants ~ 70 models) on a 327k-row panel with high-cardinality director\nFE ran ~55 s/model sequentially — ~65 min wall — on an RTX 5080 machine with\n`demeaner_backend=\"cupy64\"` on every call. The GPU was NOT the bottleneck.\n\n## Context / Trigger Conditions\n\n- Measured signature (verified 2026-07-21, H5 seat-loss rerun): job process at\n  ~1.4 cores CPU (37.7 CPU-min in 27 wall-min), `nvidia-smi` 0% utilization\n  with ~4 GB resident (cupy context loaded, idle), one pyfixest singleton\n  warning per completed model ticking by in the log.\n- Any orchestration prompt that asks a worker to \"rerun every headline cell\n  under variants A/B/C\" without specifying execution structure.\n\n## Solution\n\n1. Diagnose before blaming the GPU: check process CPU-minutes vs wall-clock\n   (~1 core => serial CPU-bound) and GPU utilization (near 0% => demeaning is\n   not the constraint). The cupy64 kwarg is still correct; it just cannot fix\n   a CPU-dominated pipeline.\n2. Shard the GRID, not the data: split the model list across N OS processes\n   (`--shard i --nshards N` over the model index, one output part-file each,\n   merge step at the end), N ~ cores-4. Models are independent — this is the\n   Execution Style process-sharding pattern applied to regressions.\n3. Amortize fixed costs inside a shard: build the panel/interactions ONCE per\n   variant and reuse; where specs share RHS/FE, use pyfixest multiple-\n   estimation syntax (multiple depvars / sw()/csw() stepwise) so one model\n   matrix serves several reported cells.\n4. Orchestrator rule: put the sharding mandate IN the worker prompt for any\n   grid larger than ~10 models. Workers default to sequential loops otherwise.\n5. Mid-flight call: if a sequential grid is already >1/3 done with no\n   per-model checkpoint, let it finish — restart+shard usually nets slower.\n   Grids launched fresh should checkpoint per model (append-only part file) so\n   this trade-off never binds again.\n\n## Verification\n\nSharded reruns of the same grid should show near-linear speedup up to\nmemory/RAM limits; per-model results must be byte-identical to the sequential\nrun (same seeds not needed — feols is deterministic).\n\n## Measured GPU-saturation verdict (2026-07-21 escalation experiment)\n\nA controlled escalation loop (same 327k-row seat-loss grid, N concurrent OS\nshard processes, nvidia-smi sampled every 2 s, RTX 5080) settled the question\nempirically: mean GPU utilization was **0.7% at N=4, 0.6% at N=8, and ~1% at\nN=12** (peaks 2-5%), with total VRAM flat around 4 GB. GPU saturation is\nUNATTAINABLE for pyfixest cupy64 grids — the demeaning kernel is a brief burst\ninside a CPU-bound per-model pipeline — so the correct objective is CPU-core\nsaturation via process shards, with cupy64 kept on per project rules. Two\nfurther measured costs: (1) kill-and-escalate restarting loses in-flight fits\n(throughput FELL from 1.29 to 0.64 fits/min when escalating 4->8 mid-run) — pick\nN once from cores and RAM, do not escalate live; (2) each shard holds the panel\nin RAM (~1.2 GB for a 327k-row panel; scale linearly), so cap N by free RAM\nbefore cores. Evidence: `.claude-local\\specialist-directors-us\\\nclassifier_aug_2026-07-21\\stageB_v2\\h5_seatloss_gpu\\attempts.json`.\n\n## Notes\n\n- VRAM: N concurrent cupy64 processes each hold a context (~4 GB observed on\n  a 327k x 40k-FE problem); on a 16 GB card cap GPU-sharing shards at ~3 or\n  run overflow shards with the numba default (flag them per project rules).\n- See also: [pyfixest-cupy64-absorbed-regressors] (numerical differences of\n  the cupy backend — unrelated to speed), and the global CLAUDE.md Execution\n  Style section (process-level parallelism; GIL makes threads useless here).\n","tagline":"Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run\nsequentially) that stay slow despite demeaner_backend=\"cupy64\" and an idle\nGPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row\npanel takes ~1 min/model, (2) process inspection sh","category":"research","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/pyfixest-grid-sharding","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/kennethkhoocy-pyfixest-grid-sharding#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"]},"trust":{"version":"trust-score-v5","score":69,"base_score":77,"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"],"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/pyfixest-grid-sharding","install":"npx skills add kennethkhoocy/applied-micro-skills --skill pyfixest-grid-sharding","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 pyfixest-grid-sharding","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":["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":["research","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":["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":64,"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":["Low GitHub adoption signal","64/100 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":["Low GitHub adoption signal"],"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":["Low GitHub adoption signal","64/100 agent safety score"]},"eval":{"version":"openagentskill-skill-eval-v1","status":"review","score":73,"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: Good trust signals with a few areas worth checking before rollout.","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","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 pyfixest-grid-sharding before installing it in an agent workflow","research","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 pyfixest-grid-sharding"]},{"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 pyfixest-grid-sharding"]},{"id":"trust_score","label":"Trust score","status":"warn","score":77,"required_for_auto_install":true,"detail":"Good trust signals with a few areas worth checking before rollout.","evidence":["Strong shortlist","47 GitHub stars","MIT"]},{"id":"audit_score","label":"Audit score","status":"warn","score":80,"required_for_auto_install":true,"detail":"Needs review","evidence":["Low GitHub adoption signal"]},{"id":"agent_safety_gate","label":"Agent safety gate","status":"warn","score":64,"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.","Low GitHub adoption signal"]},{"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-pyfixest-grid-sharding/evals","api":"/api/agent/evals?slug=kennethkhoocy-pyfixest-grid-sharding","text":"/api/agent/evals?slug=kennethkhoocy-pyfixest-grid-sharding&format=text"}},"agent_readable_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"kennethkhoocy-pyfixest-grid-sharding","name":"pyfixest-grid-sharding","description":"Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run\nsequentially) that stay slow despite demeaner_backend=\"cupy64\" and an idle\nGPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row\npanel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and\nnvidia-smi shows ~0% GPU utilization with a resident cupy context, (3)\nplanning any worker prompt that will run a model grid (robustness variants x\nFE structures x domains). Root cause: per-model CPU-side single-threaded\nfixed costs (formulaic model-matrix build, interaction construction,\nsingleton detection, cluster vcov) dominate wall time; GPU demeaning is a\nsmall slice. Fix: shard the model grid across OS processes and/or use\npyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT.","category":"research","url":"https://www.openagentskill.com/skills/kennethkhoocy-pyfixest-grid-sharding","repository":"https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/pyfixest-grid-sharding","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 local resources","Run repeatable desktop actions"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add kennethkhoocy/applied-micro-skills --skill pyfixest-grid-sharding","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-pyfixest-grid-sharding"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"pyfixest-grid-sharding\" agent skill from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/pyfixest-grid-sharding. 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: Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run sequentially) that stay slow despite demeaner_backend=\"cupy64\" and an idle GPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row panel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and nvidia-smi shows ~0% GPU utilization with a resident cupy context, (3) planning any worker prompt that will run a model grid (robustness variants x FE structures x domains). Root cause: per-model CPU-side single-threaded fixed costs (formulaic model-matrix build, interaction construction, singleton detection, cluster vcov) dominate wall time; GPU demeaning is a small slice. Fix: shard the model grid across OS processes and/or use pyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT. 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-pyfixest-grid-sharding\",\"task\":\"Install pyfixest-grid-sharding\",\"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 \"pyfixest-grid-sharding\" as a Claude Code skill from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/pyfixest-grid-sharding. 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: Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run sequentially) that stay slow despite demeaner_backend=\"cupy64\" and an idle GPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row panel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and nvidia-smi shows ~0% GPU utilization with a resident cupy context, (3) planning any worker prompt that will run a model grid (robustness variants x FE structures x domains). Root cause: per-model CPU-side single-threaded fixed costs (formulaic model-matrix build, interaction construction, singleton detection, cluster vcov) dominate wall time; GPU demeaning is a small slice. Fix: shard the model grid across OS processes and/or use pyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT. 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-pyfixest-grid-sharding\",\"task\":\"Install pyfixest-grid-sharding\",\"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 \"pyfixest-grid-sharding\" from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/pyfixest-grid-sharding 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: Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run sequentially) that stay slow despite demeaner_backend=\"cupy64\" and an idle GPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row panel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and nvidia-smi shows ~0% GPU utilization with a resident cupy context, (3) planning any worker prompt that will run a model grid (robustness variants x FE structures x domains). Root cause: per-model CPU-side single-threaded fixed costs (formulaic model-matrix build, interaction construction, singleton detection, cluster vcov) dominate wall time; GPU demeaning is a small slice. Fix: shard the model grid across OS processes and/or use pyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT. 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-pyfixest-grid-sharding\",\"task\":\"Install pyfixest-grid-sharding\",\"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-pyfixest-grid-sharding/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/kennethkhoocy-pyfixest-grid-sharding"},"trust":{"score":77,"label":"Strong shortlist","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/pyfixest-grid-sharding","install":"npx skills add kennethkhoocy/applied-micro-skills --skill pyfixest-grid-sharding","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":["research","agent-skill"],"known_risks":["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":80,"risk_level":"needs_review","risk_label":"Needs review","warnings":["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","Quality score needs review","GitHub adoption: 47 GitHub stars","Stars/forks activity: 47 stars, 0 forks; issue activity unavailable in current metadata","Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface"],"agent_contract":{"task_input":"Use pyfixest-grid-sharding in an agent workflow","recommended_action":"Require human approval before installing into a real workspace.","install_policy":"review","minimum_review_before_use":["Trust: 77/100 Strong shortlist","Audit: 80/100 Needs review","Safety: 64/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"kennethkhoocy-pyfixest-grid-sharding (pyfixest-grid-sharding)","install_command":"npx skills add kennethkhoocy/applied-micro-skills --skill pyfixest-grid-sharding","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-pyfixest-grid-sharding","task":"Use pyfixest-grid-sharding 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-pyfixest-grid-sharding","api":"https://www.openagentskill.com/api/agent/skills/kennethkhoocy-pyfixest-grid-sharding","audit":"https://www.openagentskill.com/skills/kennethkhoocy-pyfixest-grid-sharding/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=kennethkhoocy-pyfixest-grid-sharding&task=Use%20pyfixest-grid-sharding%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20pyfixest-grid-sharding%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20pyfixest-grid-sharding%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/kennethkhoocy-pyfixest-grid-sharding/install","manifest":"https://www.openagentskill.com/api/registry/manifest/kennethkhoocy-pyfixest-grid-sharding"}},"machine_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"kennethkhoocy-pyfixest-grid-sharding","name":"pyfixest-grid-sharding","description":"Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run\nsequentially) that stay slow despite demeaner_backend=\"cupy64\" and an idle\nGPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row\npanel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and\nnvidia-smi shows ~0% GPU utilization with a resident cupy context, (3)\nplanning any worker prompt that will run a model grid (robustness variants x\nFE structures x domains). Root cause: per-model CPU-side single-threaded\nfixed costs (formulaic model-matrix build, interaction construction,\nsingleton detection, cluster vcov) dominate wall time; GPU demeaning is a\nsmall slice. Fix: shard the model grid across OS processes and/or use\npyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT.","category":"research","url":"https://www.openagentskill.com/skills/kennethkhoocy-pyfixest-grid-sharding","repository":"https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/pyfixest-grid-sharding","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 local resources","Run repeatable desktop actions"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add kennethkhoocy/applied-micro-skills --skill pyfixest-grid-sharding","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-pyfixest-grid-sharding"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"pyfixest-grid-sharding\" agent skill from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/pyfixest-grid-sharding. 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: Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run sequentially) that stay slow despite demeaner_backend=\"cupy64\" and an idle GPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row panel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and nvidia-smi shows ~0% GPU utilization with a resident cupy context, (3) planning any worker prompt that will run a model grid (robustness variants x FE structures x domains). Root cause: per-model CPU-side single-threaded fixed costs (formulaic model-matrix build, interaction construction, singleton detection, cluster vcov) dominate wall time; GPU demeaning is a small slice. Fix: shard the model grid across OS processes and/or use pyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT. 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-pyfixest-grid-sharding\",\"task\":\"Install pyfixest-grid-sharding\",\"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 \"pyfixest-grid-sharding\" as a Claude Code skill from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/pyfixest-grid-sharding. 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: Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run sequentially) that stay slow despite demeaner_backend=\"cupy64\" and an idle GPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row panel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and nvidia-smi shows ~0% GPU utilization with a resident cupy context, (3) planning any worker prompt that will run a model grid (robustness variants x FE structures x domains). Root cause: per-model CPU-side single-threaded fixed costs (formulaic model-matrix build, interaction construction, singleton detection, cluster vcov) dominate wall time; GPU demeaning is a small slice. Fix: shard the model grid across OS processes and/or use pyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT. 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-pyfixest-grid-sharding\",\"task\":\"Install pyfixest-grid-sharding\",\"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 \"pyfixest-grid-sharding\" from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/pyfixest-grid-sharding 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: Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run sequentially) that stay slow despite demeaner_backend=\"cupy64\" and an idle GPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row panel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and nvidia-smi shows ~0% GPU utilization with a resident cupy context, (3) planning any worker prompt that will run a model grid (robustness variants x FE structures x domains). Root cause: per-model CPU-side single-threaded fixed costs (formulaic model-matrix build, interaction construction, singleton detection, cluster vcov) dominate wall time; GPU demeaning is a small slice. Fix: shard the model grid across OS processes and/or use pyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT. 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-pyfixest-grid-sharding\",\"task\":\"Install pyfixest-grid-sharding\",\"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-pyfixest-grid-sharding/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/kennethkhoocy-pyfixest-grid-sharding"},"trust":{"score":77,"label":"Strong shortlist","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/pyfixest-grid-sharding","install":"npx skills add kennethkhoocy/applied-micro-skills --skill pyfixest-grid-sharding","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":["research","agent-skill"],"known_risks":["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":80,"risk_level":"needs_review","risk_label":"Needs review","warnings":["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","Quality score needs review","GitHub adoption: 47 GitHub stars","Stars/forks activity: 47 stars, 0 forks; issue activity unavailable in current metadata","Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface"],"agent_contract":{"task_input":"Use pyfixest-grid-sharding in an agent workflow","recommended_action":"Require human approval before installing into a real workspace.","install_policy":"review","minimum_review_before_use":["Trust: 77/100 Strong shortlist","Audit: 80/100 Needs review","Safety: 64/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"kennethkhoocy-pyfixest-grid-sharding (pyfixest-grid-sharding)","install_command":"npx skills add kennethkhoocy/applied-micro-skills --skill pyfixest-grid-sharding","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-pyfixest-grid-sharding","task":"Use pyfixest-grid-sharding 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-pyfixest-grid-sharding","api":"https://www.openagentskill.com/api/agent/skills/kennethkhoocy-pyfixest-grid-sharding","audit":"https://www.openagentskill.com/skills/kennethkhoocy-pyfixest-grid-sharding/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=kennethkhoocy-pyfixest-grid-sharding&task=Use%20pyfixest-grid-sharding%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20pyfixest-grid-sharding%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20pyfixest-grid-sharding%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/kennethkhoocy-pyfixest-grid-sharding/install","manifest":"https://www.openagentskill.com/api/registry/manifest/kennethkhoocy-pyfixest-grid-sharding"}},"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":"local-desktop","title":"Local desktop"},{"slug":"browser-automation","title":"Browser automation"}]},"applicableAgents":["Claude Code","CLI","Codex","Cursor"],"install":{"ready":true,"command":"npx skills add kennethkhoocy/applied-micro-skills --skill pyfixest-grid-sharding","primaryTarget":"CLI","targetCount":4},"githubQuality":{"stars":47,"starsLabel":"47","forks":0,"license":"MIT","qualityScore":64,"trustScore":77,"auditScore":80},"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":["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","Needs review"]},"coverageTags":["Research","Research agents","agent-skill"]},"audit":{"audit_score":80,"risk_level":"needs_review","risk_label":"Needs review","quality_score":64,"trust_score":77,"maintenance_score":100,"security_score":86,"install_score":92,"warnings":["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":"local-desktop","title":"Local desktop","url":"https://www.openagentskill.com/use-cases/local-desktop"},{"slug":"browser-automation","title":"Browser automation","url":"https://www.openagentskill.com/use-cases/browser-automation"},{"slug":"github-automation","title":"GitHub automation","url":"https://www.openagentskill.com/use-cases/github-automation"}],"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 pyfixest-grid-sharding","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-pyfixest-grid-sharding","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 \"pyfixest-grid-sharding\" agent skill from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/pyfixest-grid-sharding. 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: Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run sequentially) that stay slow despite demeaner_backend=\"cupy64\" and an idle GPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row panel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and nvidia-smi shows ~0% GPU utilization with a resident cupy context, (3) planning any worker prompt that will run a model grid (robustness variants x FE structures x domains). Root cause: per-model CPU-side single-threaded fixed costs (formulaic model-matrix build, interaction construction, singleton detection, cluster vcov) dominate wall time; GPU demeaning is a small slice. Fix: shard the model grid across OS processes and/or use pyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT. 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-pyfixest-grid-sharding\",\"task\":\"Install pyfixest-grid-sharding\",\"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 \"pyfixest-grid-sharding\" as a Claude Code skill from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/pyfixest-grid-sharding. 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: Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run sequentially) that stay slow despite demeaner_backend=\"cupy64\" and an idle GPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row panel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and nvidia-smi shows ~0% GPU utilization with a resident cupy context, (3) planning any worker prompt that will run a model grid (robustness variants x FE structures x domains). Root cause: per-model CPU-side single-threaded fixed costs (formulaic model-matrix build, interaction construction, singleton detection, cluster vcov) dominate wall time; GPU demeaning is a small slice. Fix: shard the model grid across OS processes and/or use pyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT. 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-pyfixest-grid-sharding\",\"task\":\"Install pyfixest-grid-sharding\",\"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 \"pyfixest-grid-sharding\" from https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/pyfixest-grid-sharding 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: Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run sequentially) that stay slow despite demeaner_backend=\"cupy64\" and an idle GPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row panel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and nvidia-smi shows ~0% GPU utilization with a resident cupy context, (3) planning any worker prompt that will run a model grid (robustness variants x FE structures x domains). Root cause: per-model CPU-side single-threaded fixed costs (formulaic model-matrix build, interaction construction, singleton detection, cluster vcov) dominate wall time; GPU demeaning is a small slice. Fix: shard the model grid across OS processes and/or use pyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT. 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-pyfixest-grid-sharding\",\"task\":\"Install pyfixest-grid-sharding\",\"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/pyfixest-grid-sharding","github_repo":"kennethkhoocy/applied-micro-skills","version":"1.0.0","license":"MIT","urls":{"web":"https://www.openagentskill.com/skills/kennethkhoocy-pyfixest-grid-sharding","repository":"https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/pyfixest-grid-sharding","api":"/api/agent/skills/kennethkhoocy-pyfixest-grid-sharding","install_api":"/api/skills/kennethkhoocy-pyfixest-grid-sharding/install"},"meta":{"created_at":"2026-08-24T05:37:08.8026+00:00","updated_at":"2026-08-24T05:37:08.8026+00:00","agent_friendly":true}}