Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/justifi-tech/web-component-library/full-auditgit clone --depth 1 https://github.com/justifi-tech/web-component-libraryWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00987 |
| Opus 5 | $0.00000 | $0.00494 |
| Sonnet 5 | $0.00000 | $0.00197 |
| Haiku 4.5 | $0.00000 | $0.00099 |
Grade A, and why
full-audit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
91% identical to audit — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Study AGENTS.md for guidelines. Study specs/README.md to find all specs and their statuses.
Your task is to audit ALL specs (Ready and Implemented) against code, then write findings to the appropriate files.
Scope
Audit every spec with status Ready or Implemented. Skip Draft and Deprecated specs.
What counts as a finding
Only flag things that are functionally wrong — broken behavior, missing features, incorrect data, wrong types at system boundaries. The bar is high:
- Code produces wrong results or crashes → finding
- A spec-required feature is missing entirely → finding
- Types are wrong at API boundaries causing runtime errors → finding
- Code works correctly but uses a different pattern than the spec suggests → NOT a finding
- Spec wording doesn't perfectly match implementation details → NOT a finding
- Cosmetic differences (naming, formatting, ordering) → NOT a finding
- Documentation gaps in the spec → NOT a finding
Do NOT bump spec versions for documentation clarifications. If the spec wording is imprecise but the code is correct, the spec is fine. Only bump versions when the spec needs to prescribe genuinely new or changed behavior.
Process
Work through each spec sequentially. For each spec:
Step 1: Gather
Launch a research agent (model: Sonnet) to audit the spec against code. The agent:
- Reads the full spec
- Reads the code that implements it
- Reports raw findings: broken behavior, missing features, incorrect data handling
The agent applies the "what counts as a finding" bar above. It does NOT write or modify any files.
Step 2: Validate
When the agent returns findings, you validate each one yourself:
- Read the actual code for each finding — confirm or reject the claim against the source
- Cross-check against specd_work_list.md and specd_history.md to avoid duplicates (grep for the spec name in specd_history.md — never read it in full)
- For each finding, answer: "Is the code actually broken or producing wrong results?" If no, reject the finding.
- Categorize each confirmed finding:
- Code is broken / produces wrong results → specd_work_list.md item
- Spec needs to prescribe new behavior → spec update candidate (version bump required)
- Ambiguous, needs human → specd_review.md item
- Already known / in progress / duplicate → skip
- Code works fine, just different from spec wording → skip (do NOT flag)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 106 lines · 0 tokens per session scan A dba26feadf56
full-audit is a command published in the GitHub repository justifi-tech/web-component-library (5 stars, last pushed 7d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 987 tokens. A static security scan graded it A with 0 findings. It is 91% identical to audit, differing in 7 lines, and is treated as a copy.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.