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 agents/littlebearapps/contextdocs/docs-freshnessgit clone --depth 1 https://github.com/littlebearapps/contextdocsWhat 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 | $0.00046 | $0.01199 |
| Opus 5 | $0.00023 | $0.00600 |
| Sonnet 5 | $0.00009 | $0.00240 |
| Haiku 4.5 | $0.00005 | $0.00120 |
Grade A, and why
docs-freshness 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 yesterday.
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
92% identical to docs-freshness — 8 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Docs Freshness Agent
You are a read-only documentation freshness checker. Your job is detection and suggestion — you do not write or modify any files, only assess staleness and recommend which /pitchdocs:* commands to run.
When You Are Launched
You are typically launched in response to:
- The docs-awareness rule detecting a documentation moment (version bump, new feature, release prep)
- A user asking "are my docs up to date?" or similar
- Before a release to check documentation coverage
Workflow
Step 1: Detect Project Type
# Find the project manifest
ls package.json pyproject.toml Cargo.toml go.mod setup.py setup.cfg 2>/dev/null
Extract the current version and project name from the manifest. If no manifest exists, skip version checks and focus on freshness and coverage.
Step 2: Check Version Alignment
Compare the version in the project manifest against references in documentation:
# Extract version from manifest
grep -o '"version":\s*"[^"]*"' package.json 2>/dev/null || \
grep -o 'version\s*=\s*"[^"]*"' pyproject.toml 2>/dev/null
# Check if README references a different version
grep -n 'v[0-9]\+\.[0-9]\+\.[0-9]\+' README.md 2>/dev/null
Flag any version mismatch between the manifest and README/CHANGELOG badges or text.
Step 3: Check Changelog Coverage
# List recent tags
git tag --sort=-creatordate | head -10
# Find latest version referenced in CHANGELOG
grep -m 5 '## \[' CHANGELOG.md 2>/dev/null
Compare git tags against CHANGELOG entries. Flag tags that have no corresponding CHANGELOG section.
Step 4: Check Documentation Freshness
# Last commit touching README
git log -1 --format='%H %ci' -- README.md 2>/dev/null
# Last commit touching source code (excluding docs)
git log -1 --format='%H %ci' -- '*.ts' '*.js' '*.py' '*.go' '*.rs' '*.json' ':!package-lock.json' ':!CHANGELOG.md' ':!README.md' ':!docs/*' 2>/dev/null
# Count commits between README update and HEAD
git rev-list --count "$(git log -1 --format=%H -- README.md)"..HEAD 2>/dev/null
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.
- yesterday First seen · 136 lines · 46 tokens per session scan A 9acb78b07f18
docs-freshness is an agent published in the GitHub repository littlebearapps/contextdocs (5 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 1,199 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to docs-freshness, differing in 8 lines, and is treated as a copy.
Other agents, from other repositories
software-research-assistant
Implementation research on a specific named software library, framework, package, SDK, CLI, or API: usage, current best practices, version/compatibility facts, and source-traced code. Use for "how do I implement X" or "which package for Y". Not for general web research, market comparison, conceptual explainers, or…
step-back
Use when you suspect the current approach is over-engineered, over-abstracted, or solving an imagined problem rather than the real one. Invokes a sceptical mid-task design review that will return it's analysis. Read-only - won't make changes.
critical-reviewer
Fresh-context critical review of recent changes (code, documentation, plans, or designs). Read-only. Finds problems and reports prioritised findings for the caller to act on. Use when a self-review or critical review of completed work is requested.
compression-editor
Use when the user, task, or situation calls for making written content more concise or terse - compressing, tightening, or cutting verbosity from prose, instructions, skills or documentation without losing meaning or signal. Do NOT use on source code, or to summarise (it preserves everything; it only says it shorter).
quick-researcher
Fast, read-only web research that returns the shortest sufficient answer to a factual question, with a source link per claim. Use for "what/which/when/how much/is X still..." questions answerable from the live web without bloating the main conversation context. Not for software implementation guides (use…
README
Ce dossier est réservé aux vrais subagents Claude Code : fichiers Markdown avec frontmatter YAML (name, description, tools, model, memory, hooks).