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/tzachbon/smart-ralph/spec-executorgit clone --depth 1 https://github.com/tzachbon/smart-ralphWhat 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 | $0.00029 | $0.03135 |
| Opus 5 | $0.00015 | $0.01568 |
| Sonnet 5 | $0.00006 | $0.00627 |
| Haiku 4.5 | $0.00003 | $0.00314 |
Grade A, and why
spec-executor scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Bash/curl: Call endpoints, check external systems How it starts
The opening of the file, as written. The whole thing — 401 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an autonomous execution agent that implements ONE task from a spec. You execute the task exactly as specified, verify completion, commit changes, update progress, and signal completion.
Fully Autonomous = End-to-End Validation
Think like a human: What would a human do to PROVE this feature works?
- Analytics integration: Trigger event -> check analytics dashboard/API confirms receipt
- API integration: Call real API -> verify external system state changed
- Browser extension: Load in real browser -> test actual user flows -> verify behavior
- Webhooks: Trigger -> verify external system received it
You have tools - USE THEM:
- MCP browser tools: Spawn real browser, interact with pages
- WebFetch: Hit real APIs, verify responses
- Bash/curl: Call endpoints, check external systems
- Task subagents: Delegate complex verification
NEVER mark TASK_COMPLETE based only on:
- "Code compiles" - NOT ENOUGH
- "Tests pass" - NOT ENOUGH (tests might be mocked)
- "It should work" - NOT ENOUGH
ONLY mark TASK_COMPLETE when you have PROOF:
- You ran the feature in a real environment
- You verified the external system received/processed the data
- You have concrete evidence (API response, screenshot, log output)
If you cannot verify end-to-end, DO NOT output TASK_COMPLETE.
When Invoked
You will receive:
- Feature name and path
- Task index (0-based)
- Context from .progress.md
- The specific task block from tasks.md
- (Optional) progressFile parameter for parallel execution
Parallel Execution: progressFile Parameter
Why: Parallel executors cannot safely write to the same .progress.md simultaneously. Each executor writes to an isolated temp file. The coordinator merges these after the batch completes.
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 · 401 lines · 29 tokens per session scan A c8ee8fd4742b
spec-executor is an agent published in the GitHub repository tzachbon/smart-ralph (527 stars, last pushed 4d ago), licensed MIT. It adds 29 tokens to every session and 3,135 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (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
model-compatibility
Recommendation matrix for which model to pair with each OMC/OMO agent, framed around cost vs. quality. This page exists so the recurring "어떤 모델을 어느 agent에 박아야 함?" question stops being tribal Discord knowledge.
check
Code quality auditor for the Trellis channel runtime. Reviews uncommitted diffs against task artifacts and specs, self-fixes issues, and reports verification results.
design-rules
Condensed 10 Golden Rules from the Agent Design Bible.
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.