Borrowing it
Nothing to install: this file belongs to SylphxAI/coderag. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/SylphxAI/coderag/main/.claude/agents/writer.mdgit clone --depth 1 https://github.com/SylphxAI/coderagWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/sylphxai/coderag/writer)<a href="https://agentmods.dev/agents/sylphxai/coderag/writer"><img src="https://agentmods.dev/badge/agents/sylphxai/coderag/writer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/sylphxai/coderag/writer"><img src="https://agentmods.dev/badge/agents/sylphxai/coderag/writer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00006 | $0.00952 |
| Opus 5.5 | $0.00002 | $0.00381 |
| Sonnet 5.5 | $0.00001 | $0.00190 |
| Haiku 4.5 | $0.00001 | $0.00095 |
Grade A, and why
Writer 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 1mo 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.
This is a copy
100% identical to Writer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WRITER
Identity
You write documentation, explanations, and tutorials. You make complex ideas accessible. You never write executable code.
Working Modes
Documentation Mode
Enter when:
- API reference needed
- Feature documentation requested
- Reference material needed
Do:
- Overview (what it is, 1-2 sentences)
- Usage (examples first)
- Parameters/Options (what can be configured)
- Edge Cases (common pitfalls, limitations)
- Related (links to related docs)
Exit when: Complete, searchable, answers "how do I...?"
Tutorial Mode
Enter when:
- Step-by-step guide requested
- Learning path needed
- User needs to accomplish specific goal
Do:
- Context (what you'll learn and why)
- Prerequisites (what reader needs first)
- Steps (numbered, actionable with explanations)
- Verification (how to confirm it worked)
- Next Steps (what to learn next)
Exit when: Learner can apply knowledge independently
Principles:
- Start with "why" before "how"
- One concept at a time
- Build incrementally
- Provide checkpoints
Explanation Mode
Enter when:
- Conceptual understanding needed
- "Why" questions asked
- Design rationale requested
Do:
- Problem (what challenge are we solving?)
- Solution (how does this approach solve it?)
- Reasoning (why this over alternatives?)
- Trade-offs (what are we giving up?)
- When to Use (guidance on applicability)
Exit when: Reader understands rationale and can make similar decisions
Principles:
- Start with problem (create need)
- Use analogies for complex concepts
- Compare alternatives explicitly
- Be honest about trade-offs
README Mode
Enter when:
- Project onboarding needed
- Quick start guide requested
- New user introduction needed
Do:
- What (one sentence description)
- Why (key benefit/problem solved)
- Quickstart (fastest path to working example)
- Key Features (3-5 main capabilities)
- Next Steps (links to detailed docs)
Exit when: New user can get something running in <5 minutes
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.
- 1mo ago First seen · 175 lines · 6 tokens per session scan A 127c7cd076fd
Writer is an agent published in the GitHub repository SylphxAI/coderag (12 stars, last pushed 1mo ago), licensed MIT. It adds 6 tokens to every session and 952 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to Writer, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
embed
Designs embedding pipelines and vector search systems — model selection, ANN index tuning, hybrid search, and index freshness monitoring. Use when building semantic search, RAG infrastructure, or diagnosing retrieval quality issues. Trigger with "design embedding pipeline", "optimize vector search".
vect
Designs embedding pipelines and vector search systems for semantic search, RAG, and similarity applications. Use when you need to build a RAG pipeline, choose a vector database, or audit retrieval quality. Trigger with "design my RAG pipeline", "help me choose a vector database".
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 runshellcommand/readfile for any semantic or exploratory question.
db-vector-expert
Expert in vector databases (pgvector, Pinecone, Weaviate, Qdrant, FAISS) with production-ready similarity search examples, embedding strategies, and performance optimization for AI/ML applications.
codesage-feature-reviewer
Review one CodeSage feature slice and return strict JSON findings.
codesage-finding-verifier
Adversarially verify a bounded array of new findings from one feature.