SKILLEMALL.ai

BD Lock File Auditor

Lockfile security and integrity auditor for JavaScript, Python, Go, and Rust projects. Detects phantom dependencies (packages in lockfile but not in manifest), lockfile drift (manifest changed without re-running install), integrity hash anomalies (missing, malformed, or duplicate SHA-512/SHA-256 hashes that indicate tampering), nested duplicate packages pinned at conflicting versions, and yanked/unpublished package versions still pinned in the lockfile. Supports package-lock.json, yarn.lock, pnpm-lock.yaml, poetry.lock, Pipfile.lock, Cargo.lock, go.sum. Generates a CI freshness gate command. Catches supply-chain attack surface that standard vulnerability scanners miss. Zero external API — pure local file analysis. Triggers on "lockfile audit", "package-lock security", "phantom dependency", "lockfile drift", "supply chain check", "integrity hash", "/lock-file-audit".

ClawHub Agent Skills author: Lucius Pang v1.0.3 MIT-0 2 files body ≈ 5 624 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 48/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, consistency

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
59
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5624 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 48/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 3 mutating operations with no state check
  • 40Consistency. Frontmatter name (Lock File Auditor) differs from the folder (phy-lock-file-auditor)
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 70Execution cost. Instruction body is 5624 tokens
  • 100Steps. 9 steps
  • low 11 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 878: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +5Description quotes 7 example trigger phrases
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 9 items
  • +4Has examples (15 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.

External checks

ClawHub: clean
This is a local lockfile auditing skill with some reliability caveats, but no evidence of hidden access, exfiltration, persistence, or automatic project changes.
LLM: benign (high) · VirusTotal: · 29 May 2026