Borrowing it
Nothing to install: this file belongs to ambient-code/platform. 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/ambient-code/platform/main/.claude/agents/runner-review.mdgit clone --depth 1 https://github.com/ambient-code/platformWrote 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/ambient-code/platform/runner-review)<a href="https://agentmods.dev/agents/ambient-code/platform/runner-review"><img src="https://agentmods.dev/badge/agents/ambient-code/platform/runner-review/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/ambient-code/platform/runner-review"><img src="https://agentmods.dev/badge/agents/ambient-code/platform/runner-review.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 | $0.00040 | $0.00390 |
| Opus 5.5 | $0.00016 | $0.00156 |
| Sonnet 5.5 | $0.00008 | $0.00078 |
| Haiku 4.5 | $0.00004 | $0.00039 |
Grade A, and why
runner-review 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- runner-review — 100% identical, 0 lines differ
What it actually says
Runner Review Agent
Review runner Python code against documented conventions.
Context
No runner-specific DEVELOPMENT.md exists yet. Review against general Python best practices and the patterns visible in components/runners/ambient-runner/src/.
Checks
R1: Proper async patterns (Major)
No blocking calls (open(), requests., time.sleep()) inside async functions. Use aiofiles, httpx, asyncio.sleep().
R2: Credential handling (Blocker)
No hardcoded credential values. Credentials loaded from environment or K8s secrets. No credentials in log statements.
R3: Error propagation from subprocess (Critical)
Subprocess calls must propagate errors, not swallow them. Return codes checked, errors raised or logged with context.
R4: No hardcoded secrets or API keys (Blocker)
grep -rn "sk-\|api_key=\|password=" components/runners/ambient-runner/ --include="*.py" | grep -v "_test\|test_\|example\|mock"
Output Format
# Runner Review
## Summary
[1-2 sentence overview]
## Findings
### Blocker
[Must fix — or "None"]
### Critical
[Should fix — or "None"]
### Major
[Important — or "None"]
### Minor
[Nice-to-have — or "None"]
## Score
[X/4 checks passed]
Each finding includes: file:line, problem description, convention violated, suggested fix.
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 · 69 lines · 40 tokens per session scan A ac3a4e6ca435
runner-review is an agent published in the GitHub repository ambient-code/platform (131 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 390 once invoked, about $0.0002 per session on Opus 5.5. 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
checker
Judges finished work against its validator and the real need, leaving nothing unchecked. Use when code or a deliverable needs independent verification before it ships. Never edits the work, never implements the fix.
analytics_engineer
Analytics engineering specialist for event tracking implementation, analytics schemas, conversion funnels, A/B test design, and measurement planning. Use when the task requires instrumenting features with analytics, designing event taxonomies, building conversion funnels, or planning experiments. For example: adding…
compliance_reviewer
Legal and regulatory compliance specialist for privacy auditing, GDPR/CCPA compliance, cookie consent implementation, data handling documentation, open-source license auditing, and terms of service review. Use when the task requires regulatory compliance assessment, privacy policy review, cookie consent architecture…
i18n_specialist
Internationalization specialist for i18n architecture, string extraction, locale management, pluralization rules, RTL support, and date/number/currency formatting. Use when the task requires internationalizing an application, setting up locale file structures, extracting hardcoded strings, or adding right-to-left…
mobile_engineer
Mobile engineering specialist for iOS, Android, React Native, and Flutter feature work. Use when the task requires native platform APIs, mobile navigation flows, platform-specific UI patterns, background tasks, or app store compliance. For example: building a push notification handler, wiring biometric auth…
product_manager
Product management specialist for requirements gathering, PRDs, user stories, feature prioritization, and competitive analysis. Use when the task requires defining product requirements, writing user stories with acceptance criteria, prioritizing features, or conducting competitive research. For example: writing a PRD…