Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Sivan757/dsh-agent-plugins-marketnpx agentmods add skills/sivan757/dsh-agent-plugins-market/agents-md-auditWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sivan757/dsh-agent-plugins-market/agents-md-audit)<a href="https://agentmods.dev/skills/sivan757/dsh-agent-plugins-market/agents-md-audit"><img src="https://agentmods.dev/badge/skills/sivan757/dsh-agent-plugins-market/agents-md-audit/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sivan757/dsh-agent-plugins-market/agents-md-audit"><img src="https://agentmods.dev/badge/skills/sivan757/dsh-agent-plugins-market/agents-md-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00076 | $0.01428 |
| Opus 5.5 | $0.00030 | $0.00571 |
| Sonnet 5.5 | $0.00015 | $0.00286 |
| Haiku 4.5 | $0.00008 | $0.00143 |
Grade A, and why
agents-md-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.
Copies of this mod
1 near-identical copy found in the catalogue:
- ag-md-improver — 88% identical, 23 lines differ
How it starts
The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md Improver
Audit, evaluate, and improve AGENTS.md files across a codebase to ensure DeepSeek Harness has optimal project context.
This skill can write to AGENTS.md files. After presenting a quality report and getting user approval, it updates AGENTS.md files with targeted improvements.
Workflow
Phase 1: Discovery
Find all AGENTS.md files in the repository:
find . -name "AGENTS.md" -o -name "AGENTS.local.md" 2>/dev/null | head -50
File Types & Locations:
| Type | Location | Purpose |
|---|---|---|
| Project root | ./AGENTS.md |
Primary project context (checked into git, shared with team) |
| Local overrides | ./AGENTS.local.md |
Personal/local settings (gitignored, not shared) |
| Global defaults | ~/.dsh/AGENTS.md |
User-wide defaults across all projects |
| Package-specific | ./packages/*/AGENTS.md |
Module-level context in monorepos |
| Subdirectory | Any nested location | Feature/domain-specific context |
Note: The agent auto-discovers AGENTS.md files in parent directories, making monorepo setups work automatically.
Phase 2: Quality Assessment
For each AGENTS.md file, evaluate against quality criteria. See references/quality-criteria.md for detailed rubrics.
Quick Assessment Checklist:
| Criterion | Weight | Check |
|---|---|---|
| Commands/workflows documented | High | Are build/test/deploy commands present? |
| Architecture clarity | High | Can the agent understand the codebase structure? |
| Non-obvious patterns | Medium | Are gotchas and quirks documented? |
| Conciseness | Medium | No verbose explanations or obvious info? |
| Currency | High | Does it reflect current codebase state? |
| Actionability | High | Are instructions executable, not vague? |
Quality Scores:
- A (90-100): Comprehensive, current, actionable
- B (70-89): Good coverage, minor gaps
- C (50-69): Basic info, missing key sections
- D (30-49): Sparse or outdated
- F (0-29): Missing or severely outdated
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 179 lines · 76 tokens per session scan A 0fb791f43a12
agents-md-audit is a skill published in the GitHub repository Sivan757/dsh-agent-plugins-market (13 stars, last pushed today), licensed MIT. It adds 76 tokens to every session and 1,428 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-10-18.
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