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/littlebearapps/contextdocs/context-verifygit 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 | $0.00034 | $0.00527 |
| Opus 5 | $0.00017 | $0.00264 |
| Sonnet 5 | $0.00007 | $0.00105 |
| Haiku 4.5 | $0.00003 | $0.00053 |
Grade A, and why
context-verify 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.
What it actually says
/context-verify
Validate the quality and freshness of AI context files in the current project. Scores signal-to-noise ratio, checks line budgets, detects stale paths, verifies that bridge files stay consistent with AGENTS.md, and flags MEMORY.md drift.
Behaviour
- Load the
context-verifyskill for the full verification framework and scoring rubric - Run all verification checks against existing context files
- Calculate and report the context health score
Arguments
- No arguments: Run full verification with interactive report
ci: Output machine-readable format for CI/CD pipelines (exit code 1 on failures)ci --min-score N: Fail if score falls below threshold N
Output
AI Context Health: 80/100 (B — Minor tuning needed)
Breakdown:
Line Budget: 18/20 (-2 CLAUDE.md bridge restates AGENTS commands)
Signal Quality: 17/20 (-3 AGENTS.md has file tree)
Path Accuracy: 16/20 (-2 .cursorrules references src/old.ts, -2 legacy .cursorrules without .cursor/rules/)
Consistency: 13/15 (-2 CLAUDE.md missing @AGENTS.md)
Freshness: 12/15 (-3 copilot-instructions.md stale 90+ days)
Context Load: 4/10 (-3 Cursor 5,400 tokens, -3 Cline 5,200 tokens — over warning)
Checks: 16 run (line budgets, signal quality, stale paths, AGENTS-to-bridge consistency,
MEMORY.md drift, Context Guard status, context load, @import paths, rule path-scopes,
rule symlinks, .mcp.json, agent memory hygiene, plugin manifest, modern Cursor layout,
modern Cline layout, Copilot bridge optionality)
To reach grade A (90+): Migrate to .cursor/rules/agents.mdc (+2), remove file tree (+3),
restore @AGENTS.md import (+2), fix stale path (+2).
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 · 48 lines · 34 tokens per session scan A e4ca44f13a4f
context-verify is a command published in the GitHub repository littlebearapps/contextdocs (5 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 527 once invoked, about $0.0002 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 2026-08-31.
Other commands, from other repositories
compact-prep
Ask the agent to prepare for conversation compaction by updating any relevant state and providing guidance for the compaction agent and to kick off the session there after.
score
Run bun-sticky on the current directory to check FAF score.
test
Run the championship-grade test suite and report results.
save
Save this conversation as a new or existing reusable context.
brownfield-map
Run a complete brownfield analysis on the codebase and generate MASTER.md, summaries, risk scores, and all derived analytics.
checklist
Generate a custom checklist for the current feature based on user requirements.