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oss-forensics-orchestration

Orchestrates multi-agent forensic investigations on public GitHub repositories, coordinating parallel evidence collection, hypothesis formation, verification, and report generation.

Quality

79%

Does it follow best practices?

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SecuritybySnyk

Low

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tessl review fix ./.claude/skills/oss-forensics/orchestration/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

77%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A strong orchestration skill: the workflow is unambiguous, validation and retry loops are explicit, and guidance is concrete enough to execute directly. The main weaknesses are moderate redundancy (Critical Rules, Example Execution) and a monolithic single-file layout with external script references that are not shipped in the bundle.

Suggestions

Move the per-agent Task prompt templates and evidence-request dispatch rules into a references/ file (e.g., references/agent-prompts.md) so SKILL.md stays a lean overview.

Trim the 'Critical Rules' section, which restates constraints already embedded in the phase specifications, and shorten the Example Execution recap.

Either ship the referenced scripts (init_investigation.py, raptor-may-ask) in the bundle's scripts/ directory or document where they come from, so the skill is self-contained and verifiable.

DimensionReasoningScore

Conciseness

The phases are lean, assume Claude's competence, and explain no background concepts — no padding about what GitHub or forensics is. Not a 5 because the 'Critical Rules' section restates constraints already enforced by the phase specs, and the 'Example Execution' recap plus Python-flavored loop pseudocode add redundant tokens that could be trimmed.

4 / 5

Actionability

Mostly executable: an exact init-script command, concrete per-agent Task prompt templates with workdir/targets placeholders, flags with defaults ('--max-followups 3 --max-retries 3'), and a per-case error-handling table. Minor gaps: the loop logic is pseudocode ('find_latest_file', 'evidence_request_file_exists') rather than executable code, and paths like '.claude/skills/oss-forensics/github-evidence-kit/scripts/init_investigation.py' and 'libexec/raptor-may-ask' reference components outside this bundle that cannot be verified here.

4 / 5

Workflow Clarity

A clearly sequenced 8-phase pipeline with explicit validation checkpoints and feedback loops: Phase 0 stops if prerequisites fail, Phase 4 runs a dedicated evidence verifier, Phase 5 is a confirm/rebuttal retry loop with limits, and there is a concrete Error Handling section. This matches the top anchor — clear sequence, explicit validation, error-recovery loops, and a Critical Rules checklist.

5 / 5

Progressive Disclosure

No bundle files exist (no references/, scripts/, or assets/), so this 288-line skill is fully inline with well-organized phase sections — but content that would naturally live in separate files (agent prompt templates, evidence-request dispatch rules, error-handling matrix) is inlined in the overview, and the scripts it does reference (init_investigation.py, raptor-may-ask) are not part of this bundle. Structure is present but organization into one level-deep references is not.

3 / 5

Total

16

/

20

Passed

Description

70%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A well-written third-person description that names the domain and enumerates concrete orchestration actions with excellent distinctiveness. Its one real deficiency is the complete absence of a 'when to use' trigger clause, which both caps completeness and limits its discoverability for users who would benefit from it.

Suggestions

Append a 'Use when...' clause naming the natural trigger cases, e.g., 'Use when investigating suspicious commits, actors, or activity on a public GitHub repository, or when a vendor report alleges malicious open-source activity.'

Include the distinctive evidence sources (GH Archive, Wayback Machine, local git dangling commits, vendor-report IOC extraction) so users searching on those terms can find the skill.

Add common synonyms such as 'open-source', 'OSS', or 'supply-chain compromise' to broaden natural trigger coverage.

DimensionReasoningScore

Specificity

Lists several concrete actions — 'coordinating parallel evidence collection, hypothesis formation, verification, and report generation' — in the named domain of 'public GitHub repositories'. Not a 5 because the evidence sources that distinguish the skill (GH Archive, Wayback, local git, IOC extraction) are absent, leaving minor coverage gaps.

4 / 5

Completeness

Has a clear 'what' (orchestrates investigation phases) but no 'Use when...' clause or equivalent trigger guidance, which caps completeness at 3 per the rubric guideline. It is a strong, well-formed 'what', but 'when' is entirely absent rather than weakly implied.

3 / 5

Trigger Term Quality

Good natural keywords: 'forensic investigations', 'GitHub repositories', 'evidence collection', 'report'. A user asking for repo forensics would plausibly say these. Missing common synonyms such as 'open-source', 'OSS', 'supply-chain', or 'security incident', so not 5.

4 / 5

Distinctiveness Conflict Risk

Clear niche — multi-agent forensic orchestration of public GitHub repositories — with distinct trigger vocabulary that no generic skill would share. Overlap risk with adjacent skills (e.g., single-agent code review or general security analysis) is minimal.

5 / 5

Total

16

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

gadievron/raptor

Path

.claude/skills/oss-forensics/orchestration/SKILL.md

Reviewed

Table of Contents

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