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.
git clone --depth 1 https://github.com/raccioly/docguardWrote 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/commands/raccioly/docguard/fix)<a href="https://agentmods.dev/commands/raccioly/docguard/fix"><img src="https://agentmods.dev/badge/commands/raccioly/docguard/fix/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/commands/raccioly/docguard/fix"><img src="https://agentmods.dev/badge/commands/raccioly/docguard/fix.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 | $0.00018 | $0.00625 |
| Opus 5.5 | $0.00007 | $0.00250 |
| Sonnet 5.5 | $0.00004 | $0.00125 |
| Haiku 4.5 | $0.00002 | $0.00063 |
Grade A, and why
fix 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DocGuard Fix
DocGuard splits drift into two kinds and is explicit about which is which.
- Mechanical (deterministic, no AI): apply with
docguard fix --write. Covers removing endpoints documented but absent in code, refreshing stale "N validators" counts, replacing stale version references, inserting a missing## [Unreleased]. - Agent (needs judgment): content rewrites — e.g. updating an X-Ray section to CloudWatch, writing a new endpoint's request/response block.
Running DocGuard
Run docguard from PATH when it is installed. Otherwise run
npx --yes [email protected], the release these instructions ship with, in its
place. Every docguard … command below means one of the two.
User Input
$ARGUMENTS
You MUST consider the user input before proceeding (if not empty).
Execution
Step 1 — Apply mechanical fixes (fast, safe, no AI)
docguard fix --write
Output lists every applied fix. Idempotent: re-running is a no-op if nothing changed.
Whole-document fixes require <!-- docguard:generated true -->. A mapped human
document permits only a unique source=code section fix; --force cannot grant
ownership.
Step 2 — Identify remaining issues by kind
docguard diagnose --format json
Each issue is tagged fixKind: mechanical (mostly handled by step 1) or
fixKind: agent. Focus on the agent ones.
Step 3 — Use the deep doc prompt for content rewrites
For each affected canonical doc, get a research-grounded prompt:
docguard fix --doc architecture
docguard fix --doc data-model
docguard fix --doc api-reference
docguard fix --doc security
docguard fix --doc test-spec
docguard fix --doc environment
Execute the research steps in each prompt: read actual code files, map modules, trace routes, extract real schemas, identify real auth patterns. Then write the sections — using real file paths, real module names, real dependencies. No placeholders.
Step 4 — Verify
docguard guard
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 Changed f087f920e099
- 3d ago Changed 9809da7f3be3
- 5d ago Changed 0bfe8dd6b220
- 6d ago Changed 2745c9b69269
- 15d ago Changed · +6 lines 7056b7c69ef8
- 1mo ago Changed · +2 lines 73b476fad3dc
- 1mo ago First seen · 75 lines · 18 tokens per session scan A 15805a872b81
fix is a command published in the GitHub repository raccioly/docguard (32 stars, last pushed yesterday), licensed MIT. It adds 18 tokens to every session and 625 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
dev-docs-update
Update dev documentation before context compaction.
dev-docs
Create a comprehensive strategic plan with structured task breakdown.
explain
Explain code or concepts clearly with practical examples and analogies.
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.