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/jnarowski/agentcmd/auditgit clone --depth 1 https://github.com/jnarowski/agentcmdWhat 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 | $0.00012 | $0.03230 |
| Opus 5 | $0.00006 | $0.01615 |
| Sonnet 5 | $0.00002 | $0.00646 |
| Haiku 4.5 | $0.00001 | $0.00323 |
Grade A, and why
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 today.
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.
How it starts
The opening of the file, as written. The whole thing — 486 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audit Codebase
Perform comprehensive codebase audit focused on developer experience and code quality. Analyzes architecture, clarity, types, duplication, errors, standards, structure, debt, dependencies, and tests. Optimized for small projects (not enterprise).
Variables
- $mode: $1 (optional, default: cleanup) - Analysis depth:
cleanup(critical+moderate only),standard(all severities),deep(comprehensive with parallel agents) - $scope: $2 (optional, default: full) - Audit scope:
full,frontend,backend,workflow,types,tests
Instructions
- Focus on small project best practices - pragmatic over enterprise patterns
- Goal: improve developer experience and code maintainability
- Generate actionable recommendations with clear solutions
- Score each section with points-based system (X/100 total)
- Prioritize refactoring by impact (high/medium/low)
- Be concise - sacrifice grammar for brevity in findings
- Report file paths with line numbers for all issues found
Workflow
-
Validate arguments
- Set mode = "cleanup" if not provided
- Set scope = "full" if not provided
- Validate mode is one of: cleanup, standard, deep
- Validate scope is one of: full, frontend, backend, workflow, types, tests
-
Deploy audit agents based on mode
- cleanup mode: Deploy 3-5 targeted agents focusing on critical+moderate issues only
- standard mode: Deploy 6-8 agents covering all severity levels
- deep mode: Deploy all 10 parallel agents with ultrathink depth
-
Filter agents by scope
- If scope = "frontend": only deploy agents 2, 3, 4, 7, 10
- If scope = "backend": only deploy agents 1, 3, 4, 5, 7, 10
- If scope = "workflow": focus agents on specified domain in apps/app/src/client/pages/projects/workflows and server/domain/workflow
- If scope = "types": only deploy agent 3
- If scope = "tests": only deploy agent 10
- If scope = "full": deploy all relevant agents
-
Synthesize results
- Aggregate findings from all agents
- Calculate total score (sum of section scores)
- Categorize issues by severity: critical, moderate, minor
- Generate prioritized refactoring plan
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.
- today First seen · 486 lines · 12 tokens per session scan A 5198fdb08e38
audit is a command published in the GitHub repository jnarowski/agentcmd (18 stars, last pushed 8mo ago), licensed MIT. It adds 12 tokens to every session and 3,230 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-01.
Other commands, from other repositories
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.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.