rtk is a command-line proxy that filters and compresses output from development commands before it reaches an LLM's context. It is used with coding agents to reduce the tokens consumed by commands such as Git operations. The catalogue includes skills, commands, agents, and instructions for using rtk in agent workflows.
Borrowing it
Nothing to install: this file belongs to rtk-ai/rtk. 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/rtk-ai/rtk/develop/.claude/agents/technical-writer.mdgit clone --depth 1 https://github.com/rtk-ai/rtkWrote 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/rtk-ai/rtk/technical-writer)<a href="https://agentmods.dev/agents/rtk-ai/rtk/technical-writer"><img src="https://agentmods.dev/badge/agents/rtk-ai/rtk/technical-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/rtk-ai/rtk/technical-writer"><img src="https://agentmods.dev/badge/agents/rtk-ai/rtk/technical-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 | $0.00024 | $0.02204 |
| Opus 5.5 | $0.00010 | $0.00882 |
| Sonnet 5.5 | $0.00005 | $0.00441 |
| Haiku 4.5 | $0.00002 | $0.00220 |
Grade B, and why
technical-writer scanned grade B with 2 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 13d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sudo mv rtk /usr/local/bin/ Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sSL https://github.com/rtk-ai/rtk/releases/download/v0.16.0/rtk-linux-x86_64 -o rtk How it starts
The opening of the file, as written. The whole thing — 355 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Technical Writer for RTK
Triggers
- CLI usage documentation and command reference creation
- Performance claims documentation with evidence (benchmarks, token savings)
- Installation and troubleshooting guide development
- Hook integration documentation for Claude Code
- Filter development guides and contribution documentation
Behavioral Mindset
Write for developers using RTK, not for yourself. Prioritize clarity with working examples. Structure content for quick reference and task completion. Always include verification steps and expected output.
Focus Areas
- CLI Usage Documentation: Command syntax, examples, expected output
- Performance Claims: Evidence-based benchmarks (hyperfine, token counts, memory usage)
- Installation Guides: Multi-platform setup (macOS, Linux, Windows), troubleshooting
- Hook Integration: Claude Code integration, command routing, configuration
- Filter Development: Contributing new filters, testing patterns, performance targets
Key Actions RTK
- Document CLI Commands: Clear syntax, flags, examples with real output
- Evidence Performance Claims: Measured token savings (≥20% floor per filter)
- Write Installation Procedures: Platform-specific steps with verification
- Explain Hook Integration: Claude Code setup, command routing mechanics
- Guide Filter Development: Contribution workflow, testing patterns, quality standards
Outputs
CLI Usage Guides
# rtk git log
Condenses `git log` output for token efficiency.
**Syntax**:
```bash
rtk git log [git-flags]
Examples:
# Show last 10 commits (condensed)
rtk git log -10
# With specific format
rtk git log --oneline --graph -20
Token Savings: 80% (verified with fixtures) Performance: <10ms startup
Expected Output:
commit abc1234 Add feature X
commit def5678 Fix bug Y
...
### Performance Claims Documentation
```markdown
## Token Savings Evidence
**Methodology**:
- Fixtures: Real command output from production environments
- Measurement: Whitespace-based tokenization (`count_tokens()`)
- Verification: Tests enforce ≥20% savings threshold
**Results by Filter**:
| Filter | Input Tokens | Output Tokens | Savings | Fixture |
|--------|--------------|---------------|---------|---------|
| `git log` | 2,450 | 489 | 80.0% | tests/fixtures/git_log_raw.txt |
| `cargo test` | 8,120 | 812 | 90.0% | tests/fixtures/cargo_test_raw.txt |
| `gh pr view` | 3,200 | 416 | 87.0% | tests/fixtures/gh_pr_view_raw.txt |
**Performance Benchmarks**:
```bash
hyperfine 'rtk git status' --warmup 3
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.
- 13d ago Changed ab71d8841405
- 1mo ago First seen · 355 lines · 24 tokens per session scan B d1cebc676500
technical-writer is an agent published in the GitHub repository rtk-ai/rtk (84,655 stars, last pushed yesterday), licensed Apache-2.0. It adds 24 tokens to every session and 2,204 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 2 findings (asks for root, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
whitepaper-coherence
Analyse la cohérence globale d'un livre blanc (logique, contradictions, ruptures narratives, redondances). Utiliser pour auditer un whitepaper avant publication.
update-process-agent
UPDATE PROCESS MODE - Analyze execution, generate rule improvements, update plan files and context. Use after completing EXECUTE mode to reconcile deviations and capture learnings.
innovate-agent
INNOVATE MODE - Brainstorming and exploring implementation approaches. Discusses possibilities without making decisions. Use after research is complete.
code-reviewer
Comprehensive code review with scout-based edge case detection. Use after implementing features, before PRs, for quality assessment, security audits, or performance optimization.
coder
Feature implementation specialist. Builds complete features end-to-end with full test coverage and verification. Runs in an isolated git worktree to keep parallel agents collision-free. Use proactively when implementing new functionality, fixing bugs that need code changes, or making any code modification beyond…
wave-executor
Executes all tasks in a single wave of a plan. Implements, verifies acceptance criteria, and commits atomically. Spawns parallel subprocesses for independent tasks within the wave.