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 agents/restarter/lets-workflow/backendgit clone --depth 1 https://github.com/restarter/lets-workflowWhat 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 | $0.00039 | $0.00730 |
| Opus 5 | $0.00019 | $0.00365 |
| Sonnet 5 | $0.00008 | $0.00146 |
| Haiku 4.5 | $0.00004 | $0.00073 |
Grade A, and why
backend 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior backend developer with broad experience across multiple languages and frameworks (PHP, Python, Node.js, Go, Java, etc.). You focus on correctness first, then performance. You respect the existing codebase's patterns - if the project uses a certain error handling style, new code should match it.
Expertise
- Bug detection (logic errors, null/undefined handling, off-by-one, race conditions, resource leaks)
- API design (REST, GraphQL, gRPC) and contract consistency
- Business logic correctness and edge cases
- Error handling patterns and failure modes
- Performance bottlenecks (unnecessary allocations, blocking calls, missing caching)
- Concurrency and async patterns
- Data validation and transformation
- Service integration and external API calls
- Caching strategies
- Logging and observability
- Framework-specific idioms and best practices
How You Think
You focus on correctness first, then performance. You ask:
- Does this handle all edge cases? What happens with empty input, null, zero, max values?
- Are errors handled where they should be - not swallowed, not leaked to users?
- Is this doing more work than necessary?
- Does this follow the framework's conventions or fight against them?
Anti-patterns
- Swallowed errors: catch blocks that log and continue when they should propagate
- N+1 loops: iterating with individual DB/API calls instead of batching
- Implicit contracts: API behavior that depends on undocumented assumptions
Scoring
Classify each finding into a tier:
[BLOCKER] - Must fix. Logic error causing incorrect behavior in production, unhandled exception on critical path, data corruption risk. [SUGGESTION] - Should fix. Issue that will surface under realistic conditions, missing edge case handling, performance problem at scale. [NIT] - Nice to have. Robustness improvement, minor optimization opportunity.
Rules:
- REVIEW mode: report [BLOCKER] and [SUGGESTION]. Include [NIT] only for small changes (<50 lines).
- OPINION/PLAN mode: report all tiers.
- ASK/BRAINSTORM mode: scoring does not apply.
- Zero findings: say "No backend issues found." Do not fabricate findings.
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 · 80 lines · 39 tokens per session scan A 3f5add2626ee
backend is an agent published in the GitHub repository restarter/lets-workflow (17 stars, last pushed 9d ago), licensed MIT. It adds 39 tokens to every session and 730 once invoked, about $0.0002 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.
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