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/knitli/toolshedWrote 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/knitli/toolshed/ctx-check)<a href="https://agentmods.dev/commands/knitli/toolshed/ctx-check"><img src="https://agentmods.dev/badge/commands/knitli/toolshed/ctx-check/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/knitli/toolshed/ctx-check"><img src="https://agentmods.dev/badge/commands/knitli/toolshed/ctx-check.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 | $0.00021 | $0.00653 |
| Opus 5.5 | $0.00008 | $0.00261 |
| Sonnet 5.5 | $0.00004 | $0.00131 |
| Haiku 4.5 | $0.00002 | $0.00065 |
Grade A, and why
ctx-check 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 1mo ago.
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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/ctx:check — Staleness Validation
Validate claims in AI context files against the actual codebase. Find what's stale, what's broken, and what's drifted from reality.
Arguments
$ARGUMENTS
- No arguments: discover all context files, then validate every memory/instruction file.
- File paths (e.g.,
/ctx:check CLAUDE.md): validate only those specific files. - "validate X against Y" or "X against Y" (e.g.,
/ctx:check CLAUDE.md against GEMINI.md): extract claims from all named files, then cross-validate — check whether the claims in each file hold true not just against the codebase but also against the other named files. Flag any disagreements as drift alongside staleness. - Ecosystem names (e.g.,
/ctx:check cursor): validate all context files belonging to those ecosystems.
Instructions
First, run discovery (same as /ctx:discover) to identify all context files — unless the user named specific files above, in which case use those directly. Then, for each memory and instruction file in scope (skip config-only files and old planning output), do the following:
Extract and validate claims
Read each file and extract every factual claim that can be checked against the codebase:
- Paths: Any file or directory path in backticks or quotes. → Does it exist?
- Versions: Semver strings, edition years, rust-version values. → Compare against manifest files (Cargo.toml, package.json, pyproject.toml, go.mod).
- Dependencies: Named packages with version constraints. → Compare against manifests and lock files.
- Symbols: Type names, function names, module names, crate names in backticks. → Search the codebase for their existence.
- Counts: "N crates", "supports N languages", "seven modules". → Count the actual items.
- Commands: Build/test/lint commands in code blocks. → Check task runner configs (mise.toml, Makefile, package.json scripts, justfile).
- Technology claims: "uses X", "built with Y", "powered by Z". → Verify the dependency/tool is actually present.
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.
- 1mo ago First seen · 48 lines · 21 tokens per session scan A d12e805696e2
ctx-check is a command published in the GitHub repository knitli/toolshed (1 stars, last pushed yesterday), licensed MIT. It adds 21 tokens to every session and 653 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 2026-08-31.
Other commands, from other repositories
skillrx
Scan AI agent plugin or skill for malicious patterns before install.
memory-compact
Run a dry run first.
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.
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.