{"slug":"clawbio-analyze-fasta","name":"analyze-fasta","description":"Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics (GC, ORFs, MW, pI, GRAVY, secondary-structure fractions) with Biopython, and write a Markdown report plus structured JSON for downstream chaining.","long_description":"---\nname: analyze-fasta\ndescription: Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics (GC, ORFs, MW, pI, GRAVY, secondary-structure fractions) with Biopython, and write a Markdown report plus structured JSON for downstream chaining.\nlicense: MIT\nmetadata:\n  version: \"0.1.0\"\n  author: Santiago Rodriguez Salinas\n  domain: genomics\n  tags:\n    - fasta\n    - biopython\n    - sequence-analysis\n    - gc-content\n    - orf\n    - protein-properties\n    - isoelectric-point\n    - gravy\n  inputs:\n    - name: input\n      type: file\n      format:\n        - fasta\n        - fa\n        - fna\n        - faa\n      description: Single FASTA file with one or more nucleotide or protein records\n      required: true\n  outputs:\n    - name: report\n      type: file\n      format:\n        - md\n      description: Markdown report with summary table, per-sequence metrics, and disclaimer\n    - name: result\n      type: file\n      format:\n        - json\n      description: Machine-readable analysis results (sequence type, per-record metrics, summary)\n    - name: report_html\n      type: file\n      format:\n        - html\n      description: Standalone HTML rendering of the same report for visual inspection\n    - name: reproducibility\n      type: directory\n      description: Directory with commands.sh and run.json describing the exact run\n  dependencies:\n    python: \">=3.10\"\n    packages:\n      - biopython>=1.80\n  demo_data:\n    - path: example_data/demo_nucleotide.fasta\n      description: Synthetic ~720 bp nucleotide sequence with a small ORF (CC0, no real organism)\n    - path: example_data/demo_protein.fasta\n      description: Synthetic ~120 aa protein sequence (CC0, no real organism)\n  endpoints:\n    cli: python skills/analyze-fasta/analyze_fasta.py --input {input_file} --output {output_dir}\n  openclaw:\n    requires:\n      bins:\n        - python3\n      env:\n      config:\n    always: false\n    emoji: \"🧬\"\n    homepage: https://github.com/ClawBio/ClawBio\n    os:\n      - darwin\n      - linux\n    install:\n      - kind: pip\n        package: biopython\n        bins:\n    trigger_keywords:\n      - fasta\n      - analyze fasta\n      - analiza fasta\n      - sequence analysis\n      - gc content\n      - find orfs\n      - orf finder\n      - protein properties\n      - isoelectric point\n      - gravy index\n      - protparam\n      - molecular weight protein\n      - molecular weight dna\n---\n\n# 🧬 analyze-fasta\n\nYou are **analyze-fasta**, a specialised ClawBio agent for single-FASTA inspection. Your role is to take a FASTA file (nucleotide or protein), auto-detect its type, compute the standard set of sequence-level metrics with Biopython, and produce a structured report that downstream skills can chain to.\n\n## Trigger\n\n**Fire this skill when the user says any of:**\n- \"analyze this fasta\"\n- \"analiza este fasta\"\n- \"what's the GC content of this sequence\"\n- \"find ORFs in this sequence\"\n- \"compute pI / isoelectric point of this protein\"\n- \"GRAVY index\"\n- \"protein properties from this fasta\"\n- \"summarise this fasta\"\n- \"describe this sequence\"\n\n**Do NOT fire when:**\n- The user has FASTQ reads — route to `seq-wrangler` (alignment QC).\n- The user has a VCF — route to `variant-annotation` or `clinical-variant-reporter`.\n- The user wants comparison between two FASTA — route to `genome-compare`.\n- The user wants 3D structure prediction — route to `struct-predictor`.\n\n## Why This Exists\n\n- **Without it**: Users open Biopython interactively, copy boilerplate to compute GC / ProtParam metrics, and hand-format a report. Common values get computed inconsistently across notebooks.\n- **With it**: One command turns a FASTA into a Markdown report + JSON suitable for orchestration. Detection of nucleotide vs protein is automatic. ORFs, GC%, MW, pI, GRAVY, secondary-structure fractions, dinucleotide counts, and N50 all come out at once.\n- **Why ClawBio**: Output is structured (`result.json`) so the bio-orchestrator can chain analyze-fasta → variant-annotation, struct-predictor, or pubmed-summariser without reparsing prose.\n\n## Core Capabilities\n\n1. **Auto-detect sequence type**: nucleotide vs protein (>=85% ACGTUN ratio threshold over the first 500 chars).\n2. **Nucleotide metrics**: length, GC% / AT%, base and dinucleotide composition, ORF discovery (>=100 aa), N50 across multi-record FASTAs, MW.\n3. **Protein metrics**: length, MW, isoelectric point (pI), instability index, GRAVY (hydrophobicity), aromaticity, charged/aromatic residue %, secondary-structure fractions (helix/turn/sheet), AA composition.\n\n## Scope\n\n**One skill, one task.** This skill describes a single FASTA file. It does not align, blast, fold, compare, or annotate. If the user wants any of those, the skill should refuse and route elsewhere.\n\n## Input Formats\n\n| Format | Extension | Required Fields | Example |\n|--------|-----------|-----------------|---------|\n| FASTA (nucleotide) | `.fasta`, `.fa`, `.fna` | `>header` line + ACGTUN sequence | `example_data/demo_nucleotide.fasta` |\n| FASTA (protein) | `.fasta`, `.fa`, `.faa` | `>header` line + amino-acid sequence | `example_data/demo_protein.fasta` |\n\n## Workflow\n\nWhen the user asks for FASTA analysis:\n\n1. **Validate** (prescriptive): file exists; at least one record; first record >=10 chars; <=50% Ns. Any failure → exit 1 with explicit message. Never write a partial report.\n2. **Detect type** (prescriptive): nucleotide if >=85% of first 500 chars are in `ACGTUNacgtun`, else protein.\n3. **Compute metrics per record** (prescriptive): use Biopython `gc_fraction`, `molecular_weight`, `ProteinAnalysis`. Round consistently (GC to 2 dp, MW to 1 dp, pI to 2 dp).\n4. **Generate** (prescriptive): write `result.json` (full structured data), `report.md` (human-readable), `report.html` (visual), and `reproducibility/{commands.sh,run.json}`.\n5. **Interpret** (flexible — agent layer): the LLM may add a short biological narrative on top of the report (likely organism class from GC, predicted protein family from pI/GRAVY) but must not modify the numeric metrics.\n\n## CLI Reference\n\n```bash\n# Standard usage (ClawBio convention)\npython skills/analyze-fasta/analyze_fasta.py \\\n  --input <fasta_file> --output <report_dir>\n\n# Demo mode (uses bundled synthetic nucleotide FASTA)\npython skills/analyze-fasta/analyze_fasta.py --demo --output /tmp/analyze_fasta_demo\n\n# Via ClawBio runner\npython clawbio.py run analyze-fasta --input <fasta_file> --output <dir>\npython clawbio.py run analyze-fasta --demo\n\n# Legacy modes (backward compat with the original TP1 release)\npython skills/analyze-fasta/analyze_fasta.py <file.fasta> --json\npython skills/analyze-fasta/analyze_fasta.py <file.fasta> --html out.html\n```\n\n## Demo\n\n```bash\npython clawbio.py run analyze-fasta --demo\n```\n\nExpected output: a `report.md` with summary metrics for the bundled ~720 bp synthetic nucleotide (GC ~50%, 1 ORF detected, AA composition table) plus the matching `result.json` and `reproducibility/` bundle.\n\n## Algorithm / Methodology\n\nSo an LLM agent can apply the same logic without the script:\n\n1. **Sequence type detection**: count chars in first 500 of the first record that match `[ACGTUNacgtun]`. Ratio >= 0.85 → nucleotide, else protein. (No silent fallback; if ambiguous, document in `result.json`.)\n2. **Nucleotide GC**: `gc = (G + C) / (A + T + G + C + N) * 100`. Use Biopython `gc_fraction` to match the production behaviour.\n3. **ORF discovery**: scan all 3 forward frames for `ATG ... [TAA|TAG|TGA]`. Keep ORFs with `length_bp >= 300` (>= 100 aa).\n4. **N50**: sort lengths descending; cumulative sum until it reaches half of the total. Length at that point is N50.\n5. **Protein metrics**: Biopython `ProteinAnalysis`. Strip `X` and `*` before instantiating to avoid ProtParam errors.\n6. **Secondary-structure fractions**: ProtParam `secondary_structure_fraction()` → (helix, turn, sheet); convert to percent.\n\n**Key thresholds**:\n- Min sequence length: 10 chars (source: arbitrary lower bound to reject empty/garbage input).\n- Max N ratio: 50% (source: arbitrary; below this Biopython metrics become unreliable).\n- ORF min length: 300 bp / 100 aa (source: standard convention for naive ORF finders, avoids spurious short ORFs).\n- Sequence-type detection threshold: 85% (source: heuristic that handles common ambiguity codes without misclassifying short proteins).\n\n## Example Queries\n\n- \"Analyze sample.fasta\"\n- \"Analiza este FASTA, decime el GC y los ORFs\"\n- \"What's the molecular weight of this protein?\"\n- \"Compute pI of the FASTA in /tmp/x.fa\"\n\n## Example Output\n\n```markdown\n# analyze-fasta Report\n\n**Input file:** `demo_nucleotide.fasta`\n**Analysis date:** 2026-05-05 12:00:00\n**Sequence type:** `nucleotide`\n**Total sequences:** 1\n\n## Summary\n\n| Metric | Value |\n|---|---|\n| total_sequences | 1 |\n| total_residues | 720 |\n| min_length | 720 |\n| max_length | 720 |\n| avg_length | 720.0 |\n| n50 | 720 |\n| avg_gc_content | 50.42 |\n| total_orfs | 1 |\n\n## Per-sequence metrics\n\n### 1. synthetic_demo_orf\n\n- **Description:** synthetic_demo_orf | Synthetic E. coli-like ORF\n- **Length:** 720 bp\n- **GC content:** 50.42%\n- **AT content:** 49.58%\n- **ORFs (>=100 aa):** 1\n\n---\n\n_ClawBio is a research and educational tool. It is not a medical device and does not provide clinical diagnoses. Consult a healthcare professional before making any medical decisions._\n```\n\n## Output Structure\n\n```\n<output_dir>/\n├── report.md              # Primary markdown report\n├── report.html            # Standalone visual report\n├── result.json            # Machine-readable results\n└── reproducibility/\n    ├── commands.sh        # Exact command to reproduce\n    └── run.json           # Run metadata (versions, timestamps, input size)\n```\n\n## Dependencies\n\n**Required**:\n- `biopython` >= 1.80; sequence parsing, ProtParam, gc_fraction, molecular_weight.\n\n**Optional**:\n- None. The skill is intentionally lean; pure stdlib + Biopython.\n\n## Gotchas\n\n- **The model will want to claim \"this is gene X / from organism Y\" from GC content alone.** Do not. GC is a weak signal — many taxa overlap. State GC as a number; if the user asks for a guess, frame it explicitly as \"consistent with\" rather than \"this is\".\n- **The model will treat ORFs >100 aa as proof of coding.** Do not. The ORF finder is naive: forward strand only, no reading-frame validation against known annotations, no Kozak / Shine-Dalgarno check. Frame ORFs as candidates, never confirmed.\n- **The model will silently re-interpret a sequence with many Ns as a real result.** Do not. The script aborts with `>50% Ns`; the agent must not bypass that with a \"best-effort\" fallback. Surface the failure to the user.\n- **The model will mix nucleotide and protein metrics if a multi-record FASTA mixes types.** The skill detects type from the first record only. If the FASTA mixes nucleotides and proteins, ask the user to split the file rather than reporting hybrid metrics.\n- **The model will use the script's HTML output as the primary deliverable.** Use `report.md` for chaining; the HTML is a courtesy for human inspection only.\n\n## Safety\n\n- **Local-first**: no network calls; everything runs against the local file.\n- **Disclaimer**: every `report.md` includes the standard ClawBio research-tool disclaimer.\n- **Audit trail**: every run writes `reproducibility/run.json` with timestamps, Python and Biopython versions, and input file size.\n- **No hallucinated science**: thresholds (GC, ORF, N ratio) are documented in this SKILL.md; the agent must not invent new ones.\n\n## Agent Boundary\n\nThe agent (LLM) decides whether to fire this skill, may add a short biological-context paragraph on top of the report, and may suggest follow-up skills (`struct-predictor`, `variant-annotation`, `pubmed-summariser`). The skill (Python) executes the metrics and writes the artefacts. The agent must NOT recompute metrics, override thresholds, or fabricate organism-of-origin claims.\n\n## Integration with Bio Orchestrator\n\n**Trigger conditions**: the orchestrator routes here when the input is a single `.fasta`/`","tagline":"Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics (GC, ORFs, MW, pI, GRAVY, secondary-structure fractions) with Biopython, and write a Markdown report plus structured JSON for downstream chaining.","category":"productivity","tags":["agent-skill"],"author":"ClawBio","verified":false,"attribution":{"status":"registry_indexed","statusLabel":"Registry indexed","shortLabel":"REGISTRY INDEXED","sourceLabel":"recursive skill source sync","sourceDetail":"ClawBio/ClawBio","creatorName":"ClawBio","creatorUrl":"https://github.com/ClawBio","sourceUrl":"https://github.com/ClawBio/ClawBio/tree/main/skills/analyze-fasta","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/clawbio-analyze-fasta#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. 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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: Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics (GC, ORFs, MW, pI, GRAVY, secondary-structure fractions) with Biopython, and write a Markdown report plus structured JSON for downstream chaining. 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\":\"clawbio-analyze-fasta\",\"task\":\"Install analyze-fasta\",\"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 \"analyze-fasta\" as a Claude Code skill from https://github.com/ClawBio/ClawBio/tree/main/skills/analyze-fasta. 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: Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics (GC, ORFs, MW, pI, GRAVY, secondary-structure fractions) with Biopython, and write a Markdown report plus structured JSON for downstream chaining. 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\":\"clawbio-analyze-fasta\",\"task\":\"Install analyze-fasta\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. 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Inspect the source, dependencies, and permission surface first.","install_policy":"block","minimum_review_before_use":["Trust: 69/100 Manual review","Audit: 79/100 Needs review","Safety: 39/100 Avoid automatic install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"clawbio-analyze-fasta (analyze-fasta)","install_command":"npx skills add ClawBio/ClawBio --skill analyze-fasta","risk_summary":"Needs review; Blocked for auto-install; 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":"clawbio-analyze-fasta","task":"Use analyze-fasta 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/clawbio-analyze-fasta","api":"https://www.openagentskill.com/api/agent/skills/clawbio-analyze-fasta","audit":"https://www.openagentskill.com/skills/clawbio-analyze-fasta/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=clawbio-analyze-fasta&task=Use%20analyze-fasta%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20analyze-fasta%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20analyze-fasta%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/clawbio-analyze-fasta/install","manifest":"https://www.openagentskill.com/api/registry/manifest/clawbio-analyze-fasta"}},"machine_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"clawbio-analyze-fasta","name":"analyze-fasta","description":"Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics (GC, ORFs, MW, pI, GRAVY, secondary-structure fractions) with Biopython, and write a Markdown report plus structured JSON for downstream chaining.","category":"productivity","url":"https://www.openagentskill.com/skills/clawbio-analyze-fasta","repository":"https://github.com/ClawBio/ClawBio/tree/main/skills/analyze-fasta","github_repo":"ClawBio/ClawBio"},"suited_tasks":["Research agents workflows","Claude Code teams","teams that value GitHub adoption signals","Search sources","Extract claims","Synthesize findings","Move data between tools","Transform files"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add ClawBio/ClawBio --skill analyze-fasta","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 clawbio-analyze-fasta"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"analyze-fasta\" agent skill from https://github.com/ClawBio/ClawBio/tree/main/skills/analyze-fasta. 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: Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics (GC, ORFs, MW, pI, GRAVY, secondary-structure fractions) with Biopython, and write a Markdown report plus structured JSON for downstream chaining. 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\":\"clawbio-analyze-fasta\",\"task\":\"Install analyze-fasta\",\"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 \"analyze-fasta\" as a Claude Code skill from https://github.com/ClawBio/ClawBio/tree/main/skills/analyze-fasta. 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: Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics (GC, ORFs, MW, pI, GRAVY, secondary-structure fractions) with Biopython, and write a Markdown report plus structured JSON for downstream chaining. 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\":\"clawbio-analyze-fasta\",\"task\":\"Install analyze-fasta\",\"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 \"analyze-fasta\" from https://github.com/ClawBio/ClawBio/tree/main/skills/analyze-fasta 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: Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics (GC, ORFs, MW, pI, GRAVY, secondary-structure fractions) with Biopython, and write a Markdown report plus structured JSON for downstream chaining. 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\":\"clawbio-analyze-fasta\",\"task\":\"Install analyze-fasta\",\"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/clawbio-analyze-fasta/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/clawbio-analyze-fasta"},"trust":{"score":69,"label":"Manual review","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"1.1K GitHub stars","repoActivity":"1.1K stars, 257 forks","lastPushed":"Pushed today","license":"MIT","repository":"https://github.com/ClawBio/ClawBio/tree/main/skills/analyze-fasta","install":"npx skills add ClawBio/ClawBio --skill analyze-fasta","installSafety":"standard package or runtime install path","permissionSurface":"secrets or environment access, shell or command execution","documentation":"Strong README/SKILL.md context","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":["productivity","agent-skill"],"known_risks":["The SKILL.md excerpt is truncated; full documentation may be incomplete, but the provided sections are clear.","Quality score needs review","Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access","Permission surface: secrets or environment access, shell or command execution"]},"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":79,"risk_level":"needs_review","risk_label":"Needs review","warnings":["Dependency or permission surface needs review","Permission surface may require sandboxing","The SKILL.md excerpt is truncated; full documentation may be incomplete, but the provided sections are clear.","The script uses Spanish comments and variable names, which may reduce maintainability for international contributors.","The CLI flags (--json, --html) are not fully aligned with the documented outputs (report.md, result.json, report_html, reproducibility); ensure the script generates all documented artifacts.","Quality score needs review","Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access"]},"safety_gate":{"tier":"blocked","label":"Blocked for auto-install","auto_install_policy":"block","auto_install_allowed":false,"human_review_required":true,"blocked":true,"recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first."},"quality":{"score":78,"label":"Strong"},"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","The SKILL.md excerpt is truncated; full documentation may be incomplete, but the provided sections are clear.","High-risk permission hints: Shell or command execution, Secrets or environment access","Dependency or permission surface needs review","Permission surface may require sandboxing","The script uses Spanish comments and variable names, which may reduce maintainability for international contributors.","The CLI flags (--json, --html) are not fully aligned with the documented outputs (report.md, result.json, report_html, reproducibility); ensure the script generates all documented artifacts."],"agent_contract":{"task_input":"Use analyze-fasta in an agent workflow","recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first.","install_policy":"block","minimum_review_before_use":["Trust: 69/100 Manual review","Audit: 79/100 Needs review","Safety: 39/100 Avoid automatic install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"clawbio-analyze-fasta (analyze-fasta)","install_command":"npx skills add ClawBio/ClawBio --skill analyze-fasta","risk_summary":"Needs review; Blocked for auto-install; 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":"clawbio-analyze-fasta","task":"Use analyze-fasta 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/clawbio-analyze-fasta","api":"https://www.openagentskill.com/api/agent/skills/clawbio-analyze-fasta","audit":"https://www.openagentskill.com/skills/clawbio-analyze-fasta/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=clawbio-analyze-fasta&task=Use%20analyze-fasta%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20analyze-fasta%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20analyze-fasta%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/clawbio-analyze-fasta/install","manifest":"https://www.openagentskill.com/api/registry/manifest/clawbio-analyze-fasta"}},"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":"workflow-automation","title":"Workflow automation"},{"slug":"github-automation","title":"GitHub automation"}]},"applicableAgents":["Claude Code","CLI","Codex","Cursor"],"install":{"ready":true,"command":"npx skills add ClawBio/ClawBio --skill analyze-fasta","primaryTarget":"CLI","targetCount":4},"githubQuality":{"stars":1112,"starsLabel":"1.1K","forks":257,"license":"MIT","qualityScore":78,"trustScore":69,"auditScore":79},"maintenance":{"status":"fresh","label":"Pushed today","daysSincePush":0,"lastPushedAt":"2026-08-23T08:54:13+00:00"},"risk":{"level":"needs_review","label":"Needs review","requiresReview":true,"notes":["Dependency or permission surface needs review","Permission surface may require sandboxing","The SKILL.md excerpt is truncated; full documentation may be incomplete, but the provided sections are clear.","The script uses Spanish comments and variable names, which may reduce maintainability for international contributors.","The CLI flags (--json, --html) are not fully aligned with the documented outputs (report.md, result.json, report_html, reproducibility); ensure the script generates all documented artifacts."]},"coverageTags":["Research","Research agents","productivity","agent-skill"]},"audit":{"audit_score":79,"risk_level":"needs_review","risk_label":"Needs review","quality_score":78,"trust_score":69,"maintenance_score":100,"security_score":73,"install_score":92,"warnings":["Dependency or permission surface needs review","Permission surface may require sandboxing","The SKILL.md excerpt is truncated; full documentation may be incomplete, but the provided sections are clear.","The script uses Spanish comments and variable names, which may reduce maintainability for international contributors.","The CLI flags (--json, --html) are not fully aligned with the documented outputs (report.md, result.json, report_html, reproducibility); ensure the script generates all documented artifacts.","Quality score needs review","Permission surface needs review: secrets or environment access, shell or command execution","Dependency/runtime risk: command execution surface, credential or environment access","Permission surface: secrets or environment access, shell or command execution"]},"quality_signals":{"model":"v2","star_score":21.33,"usage_score":0,"review_score":5.55,"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":"workflow-automation","title":"Workflow automation","url":"https://www.openagentskill.com/use-cases/workflow-automation"},{"slug":"github-automation","title":"GitHub automation","url":"https://www.openagentskill.com/use-cases/github-automation"},{"slug":"local-desktop","title":"Local desktop","url":"https://www.openagentskill.com/use-cases/local-desktop"}],"stacks":[{"slug":"research-report-agent","title":"Research report agent","url":"https://www.openagentskill.com/collections/research-report-agent"},{"slug":"content-growth-agent","title":"Content growth agent","url":"https://www.openagentskill.com/collections/content-growth-agent"},{"slug":"rag-knowledge-base","title":"RAG knowledge base","url":"https://www.openagentskill.com/collections/rag-knowledge-base"}],"install":"npx skills add ClawBio/ClawBio --skill analyze-fasta","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 clawbio-analyze-fasta","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 \"analyze-fasta\" agent skill from https://github.com/ClawBio/ClawBio/tree/main/skills/analyze-fasta. 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: Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics (GC, ORFs, MW, pI, GRAVY, secondary-structure fractions) with Biopython, and write a Markdown report plus structured JSON for downstream chaining. 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\":\"clawbio-analyze-fasta\",\"task\":\"Install analyze-fasta\",\"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 \"analyze-fasta\" as a Claude Code skill from https://github.com/ClawBio/ClawBio/tree/main/skills/analyze-fasta. 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: Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics (GC, ORFs, MW, pI, GRAVY, secondary-structure fractions) with Biopython, and write a Markdown report plus structured JSON for downstream chaining. 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\":\"clawbio-analyze-fasta\",\"task\":\"Install analyze-fasta\",\"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 \"analyze-fasta\" from https://github.com/ClawBio/ClawBio/tree/main/skills/analyze-fasta 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: Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics (GC, ORFs, MW, pI, GRAVY, secondary-structure fractions) with Biopython, and write a Markdown report plus structured JSON for downstream chaining. 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\":\"clawbio-analyze-fasta\",\"task\":\"Install analyze-fasta\",\"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/ClawBio/ClawBio/tree/main/skills/analyze-fasta","github_repo":"ClawBio/ClawBio","version":"1.0.0","license":"MIT","urls":{"web":"https://www.openagentskill.com/skills/clawbio-analyze-fasta","repository":"https://github.com/ClawBio/ClawBio/tree/main/skills/analyze-fasta","api":"/api/agent/skills/clawbio-analyze-fasta","install_api":"/api/skills/clawbio-analyze-fasta/install"},"meta":{"created_at":"2026-08-23T13:24:57.177433+00:00","updated_at":"2026-08-23T13:24:57.177433+00:00","agent_friendly":true}}