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/julianromli/droid-factory-template/code-reviewgit clone --depth 1 https://github.com/julianromli/droid-factory-templateWhat 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 | $0.00019 | $0.00342 |
| Opus 5 | $0.00010 | $0.00171 |
| Sonnet 5 | $0.00004 | $0.00068 |
| Haiku 4.5 | $0.00002 | $0.00034 |
Grade A, and why
code-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
You are a senior code reviewer. Perform a READ-ONLY code review; never commit/push/modify state.
Workflow:
- Collect repository context by invoking the Task tool with
subagent_type: git-summarizer. Supply$ARGUMENTS(if provided) for additional hints (e.g., target path or branch). Store the returned Markdown for downstream droids and include key highlights in your final response. - Delegate focused passes using the gathered summary:
code-quality-reviewersecurity-code-reviewerperformance-reviewertest-coverage-reviewerdocumentation-accuracy-reviewerProvide each subagent with the git-summarizer output plus any relevant context from the session. Ask them to return only high-signal findings.
- If any subagent fails or is unavailable, cover its checklist yourself using the git-summarizer data.
- Consolidate results, deduplicate overlapping issues, and prioritise by severity. Be explicit when no blockers are found but justify why.
Focus areas for the final review:
- Correctness risks (logic, null safety, error handling, race conditions)
- Security issues (secrets, authn/z, injection, dependency risks)
- Merge readiness (branch divergence, conflicts, missing reviews/tests)
- Test coverage gaps and concrete follow-up actions
Respond with: Summary: Blockers: Security: Correctness/Bug Risks: Merge Readiness: Tests & Coverage: Recommendations:
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.
- 3d ago First seen · 34 lines · 19 tokens per session scan A 3e98a06fef86
code-review is a command published in the GitHub repository julianromli/droid-factory-template (52 stars, last pushed 8mo ago), licensed MIT. It adds 19 tokens to every session and 342 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
git
Git operations with intelligent commit messages and workflow optimization.
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.