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/el-feo/ai-context/tdd-taskgit clone --depth 1 https://github.com/el-feo/ai-contextWhat 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 | $0.00025 | $0.03060 |
| Opus 5 | $0.00013 | $0.01530 |
| Sonnet 5 | $0.00005 | $0.00612 |
| Haiku 4.5 | $0.00003 | $0.00306 |
Grade A, and why
tdd-task 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.
How it starts
The opening of the file, as written. The whole thing — 419 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resolution order if omitted:
- If branch name matches
ghpm/task-<N>-*ortask-<N>-*, use N - Most recent open issue labeled
Taskassigned to @me:gh issue list -l Task -a @me -s open --limit 1 --json number -q '.[0].number' - Most recent open Task:
gh issue list -l Task -s open --limit 1 --json number -q '.[0].number'
<usage_examples> With task number:
/ghpm:tdd-task task=#42
With focus hint:
/ghpm:tdd-task task=#42 focus=unit
Auto-resolve from branch:
# On branch: ghpm/task-42-add-auth
/ghpm:tdd-task
Auto-resolve from GitHub:
# No arguments - uses most recent assigned Task
/ghpm:tdd-task
</usage_examples>
<operating_rules>
- Always create a feature branch before making changes. Never commit directly to main/master.
- No local markdown artifacts. Do not write local status files; only code changes + GitHub issue/PR updates.
- Do NOT use the TodoWrite tool to track tasks during this session.
- Do not silently expand scope. If you must, create a new follow-up Task issue and link it.
- Always provide a runnable test command in the final notes.
- Minimize noise: comment at meaningful milestones.
- All commits and PR titles MUST follow Conventional Commits format for changelog generation. </operating_rules>
<conventional_commits>
Conventional Commits Format
All commits and PR titles must follow the Conventional Commits specification to enable automated changelog generation.
Format
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 · 419 lines · 25 tokens per session scan A 03e3e8aa62bf
tdd-task is a command published in the GitHub repository el-feo/ai-context (12 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 3,060 once invoked, about $0.0001 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.
constitution
Create or update the project constitution from interactive or provided principle inputs.
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.