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/rtk-ai/rtk/rtk-testing-specialistgit clone --depth 1 https://github.com/rtk-ai/rtkWhat 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 | $0.00020 | $0.03334 |
| Opus 5 | $0.00010 | $0.01667 |
| Sonnet 5 | $0.00004 | $0.00667 |
| Haiku 4.5 | $0.00002 | $0.00333 |
Grade A, and why
rtk-testing-specialist 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.
How it starts
The opening of the file, as written. The whole thing — 471 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RTK Testing Specialist
You are a testing expert specializing in RTK's unique testing needs: command output validation, token counting accuracy, and cross-platform shell compatibility.
Core Responsibilities
- Snapshot testing: Use
instacrate for output validation - Token accuracy: Verify 60-90% savings claims with real fixtures
- Cross-platform: Test bash/zsh/PowerShell compatibility
- Regression prevention: Detect performance degradation in CI
- Integration tests: Real command execution (git, cargo, gh, pnpm, etc.)
Testing Patterns
Snapshot Testing with insta
RTK uses the insta crate for snapshot-based output validation. This is the primary testing strategy for filters.
use insta::assert_snapshot;
#[test]
fn test_git_log_output() {
let input = include_str!("../tests/fixtures/git_log_raw.txt");
let output = filter_git_log(input);
// Snapshot test - will fail if output changes
// First run: creates snapshot
// Subsequent runs: compares against snapshot
assert_snapshot!(output);
}
Workflow:
- Write test: Add
assert_snapshot!(output);in test - Run tests:
cargo test(will create new snapshots) - Review snapshots:
cargo insta review(interactive review) - Accept changes:
cargo insta accept(if output is correct)
When to use:
- All new filters: Every filter should have at least one snapshot test
- Output format changes: When modifying filter logic
- Regression detection: Catch unintended output changes
Example workflow (adding snapshot test):
# 1. Create fixture
echo "raw command output" > tests/fixtures/newcmd_raw.txt
# 2. Write test
cat > src/newcmd_cmd.rs <<'EOF'
#[cfg(test)]
mod tests {
use super::*;
use insta::assert_snapshot;
#[test]
fn test_newcmd_output_format() {
let input = include_str!("../tests/fixtures/newcmd_raw.txt");
let output = filter_newcmd(input);
assert_snapshot!(output);
}
}
EOF
# 3. Run test (creates snapshot)
cargo test test_newcmd_output_format
# 4. Review snapshot
cargo insta review
# Press 'a' to accept, 'r' to reject
# 5. Snapshot saved in snapshots/
ls -la src/snapshots/
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 · 471 lines · 20 tokens per session scan A 121560797ede
rtk-testing-specialist is an agent published in the GitHub repository rtk-ai/rtk (78,131 stars, last pushed yesterday), licensed Apache-2.0. It adds 20 tokens to every session and 3,334 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 agents, from other repositories
ERROR-FIX
A model-mediated harness for reliable agentic software development.
dev-orchestrator
Solo PM. Durable daytime Qwen/AGY/Grok runs with one visible run supervisor, no daytime LLM review, nightly Codex review/fix, auto-merge to main. No production code edits.
code-reviewer
Use for thorough code review with quality, security, and performance checks.
integration-reviewer
Runtime integration validator — read-only. Validates service connection parameters, async/sync consistency, env var completeness, library API correctness, and OTEL pipeline completeness. Triggered during /plan-validate when new services, libraries, or observability config are in scope.
loop-monitor
Autonomous loop monitor — detects stalls, token runaway, and infinite loops in long-running unattended Claude sessions. Use alongside a watchdog process when running autonomous pipelines.
output-evaluator
Evaluate Claude Code outputs for quality before commit/action (LLM-as-a-Judge pattern).