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/ooiyeefei/ccc/filegit clone --depth 1 https://github.com/ooiyeefei/cccWhat 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 | $0.00008 | $0.00487 |
| Opus 5 | $0.00004 | $0.00244 |
| Sonnet 5 | $0.00002 | $0.00097 |
| Haiku 4.5 | $0.00001 | $0.00049 |
Grade A, and why
file 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 2d 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.
What it actually says
Feature Filing
Create GitHub Issues for gaps marked "FILE" in gap analysis.
Prerequisites
-
Check GitHub CLI availability:
gh auth statusIf not authenticated: "Run
gh auth loginfirst." -
Check gap analysis exists:
- Read latest
.pm/gaps/*.mdfile - If missing: "Run
/pm:gapsfirst."
- Read latest
Process
Without Arguments - Review Mode
Walk through each gap from latest analysis:
- Show gap with score and evidence
- Ask: "FILE / WAIT / SKIP?"
- Allow score adjustments
- Save decisions to gap analysis file
With Argument - File Specific or All
If $ARGUMENTS is "all":
- File all gaps marked "FILE"
If $ARGUMENTS is specific gap ID:
- File only that gap
GitHub Issue Creation
For each gap to file:
-
Deduplication Check
gh issue list --search "[gap title]" --label "pm:feature-request" --json number,titleIf >70% match exists: Show existing issue, ask to continue
-
Create Issue using template from
references/issue-template.md:gh issue create \ --title "Feature: [Gap Name]" \ --body "[Issue template filled]" \ --label "pm:feature-request" \ --label "[winning-label]" \ --label "[priority-label]" -
Apply Labels:
- WINNING 40+:
winning:high,priority:now - WINNING 25-39:
winning:medium,priority:next - WINNING <25:
winning:low,priority:later
- WINNING 40+:
-
Save Local Copy
- Save to
.pm/requests/[issue-number].md - Include GitHub issue number for reference
- Save to
-
Return Issue URLs to user
If gh CLI Unavailable
Output markdown formatted for manual GitHub issue creation.
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.
- 2d ago First seen · 76 lines · 0 tokens per session scan A 47d05f4ade69
file is a command published in the GitHub repository ooiyeefei/ccc (483 stars, last pushed 1mo ago), licensed MIT. It adds 8 tokens to every session and 487 once invoked, about $0.0000 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 2026-08-30.
Other commands, from other repositories
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.