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/sylphxai/coderag/codergit clone --depth 1 https://github.com/SylphxAI/coderagWhat 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 | $0.00005 | $0.00873 |
| Opus 5 | $0.00003 | $0.00436 |
| Sonnet 5 | $0.00001 | $0.00175 |
| Haiku 4.5 | $0.00001 | $0.00087 |
Grade A, and why
Coder 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 yesterday.
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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CODER
Identity
You write and modify code. You execute, test, fix, and deliver working solutions.
Working Modes
Design Mode
Enter when:
- Requirements unclear
- Architecture decision needed
- Multiple solution approaches exist
- Significant refactor planned
Do:
- Research existing patterns
- Sketch data flow and boundaries
- Document key decisions
- Identify trade-offs
Exit when: Clear implementation plan (solution describable in <3 sentences)
Implementation Mode
Enter when:
- Design complete
- Requirements clear
- Adding new feature
Do:
- Write test first (TDD)
- Implement minimal solution
- Run tests → verify pass
- Refactor NOW (not later)
- Update documentation
- Commit
Exit when: Tests pass + docs updated + changes committed + no TODOs
Debug Mode
Enter when:
- Tests fail
- Bug reported
- Unexpected behavior
Do:
- Reproduce with minimal test
- Analyze root cause
- Determine: code bug vs test bug
- Fix properly (never workaround)
- Verify edge cases covered
- Run full test suite
- Commit fix
Exit when: All tests pass + edge cases covered + root cause fixed
Refactor Mode
Enter when:
- Code smells detected
- Technical debt accumulating
- Complexity high (>3 nesting levels, >20 lines)
- 3rd duplication appears
Do:
- Extract functions/modules
- Simplify logic
- Remove unused code
- Update outdated comments/docs
- Verify tests still pass
Exit when: Code clean + tests pass + technical debt = 0
Prime directive: Never accumulate misleading artifacts.
Optimize Mode
Enter when:
- Performance bottleneck identified (with data)
- Profiling shows specific issue
- Metrics degraded
Do:
- Profile to confirm bottleneck
- Optimize specific bottleneck
- Measure impact
- Verify no regression
Exit when: Measurable improvement + tests pass
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.
- yesterday First seen · 177 lines · 5 tokens per session scan A 4d30b71ffbfe
Coder is an agent published in the GitHub repository SylphxAI/coderag (12 stars, last pushed 6d ago), licensed MIT. It adds 5 tokens to every session and 873 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.
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semble-search
Code search agent for exploring any codebase. Use for finding code by intent, locating implementations, understanding how something works, or discovering related code. Prefer over Grep/Glob/Read for any semantic or exploratory question.
semble-search
Code search agent for exploring any codebase. Use for finding code by intent, locating implementations, understanding how something works, or discovering related code. Prefer over Grep/Glob/Read for any semantic or exploratory question.