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-drift)<a href="https://agentmods.dev/commands/knitli/toolshed/ctx-drift"><img src="https://agentmods.dev/badge/commands/knitli/toolshed/ctx-drift/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-drift"><img src="https://agentmods.dev/badge/commands/knitli/toolshed/ctx-drift.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 | $0.00016 | $0.00667 |
| Opus 5.5 | $0.00006 | $0.00267 |
| Sonnet 5.5 | $0.00003 | $0.00133 |
| Haiku 4.5 | $0.00002 | $0.00067 |
Grade A, and why
ctx-drift 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/ctx:drift — Cross-Document Drift Detection
Find contradictions, gaps, and inconsistencies between AI context files from different tool ecosystems.
Arguments
$ARGUMENTS
- No arguments: discover all context files, then compare every pair.
- File paths (e.g.,
/ctx:drift CLAUDE.md GEMINI.md AGENTS.md): compare only the named files against each other. At least two files are needed for a meaningful comparison. - Ecosystem names (e.g.,
/ctx:drift claude-code cursor): compare all context files belonging to those ecosystems. - Single file (e.g.,
/ctx:drift CLAUDE.md): compare that file against every other discovered context file to find where it disagrees.
Instructions
First, identify all memory and instruction files in the repo (run discovery if needed). If the user provided arguments above, restrict comparison to the specified files or ecosystems. Then compare them against each other.
Comparison process
For each pair of context files that describe the same project:
1. Identify shared topics. Do both files discuss: project architecture? Dependencies? Build commands? Directory structure? Language support? Deployment targets? Testing approach?
2. Compare factual claims on shared topics.
- Version numbers: do they cite the same versions?
- Architecture descriptions: do they describe the same patterns?
- Technology references: do they name the same tools/frameworks?
- Path references: do they point to the same locations?
- Command references: do they list the same commands?
3. Flag contradictions. Where file A explicitly says X and file B explicitly says Y about the same thing. Include both quotes and explain the conflict.
4. Flag gaps. Where file A covers a significant topic (a core dependency, a major architectural decision, a deployment model) that file B omits entirely. This usually means file B predates a change. Note which file is likely more current based on modification dates and content depth.
Also check for
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 · 60 lines · 16 tokens per session scan A 4e18e06d4635
ctx-drift is a command published in the GitHub repository knitli/toolshed (1 stars, last pushed yesterday), licensed MIT. It adds 16 tokens to every session and 667 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.