Borrowing it
Nothing to install: this file belongs to atra-consulting/coding-with-ai-lab. 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/atra-consulting/coding-with-ai-lab/main/.claude/agents/ba-reviewer.mdgit clone --depth 1 https://github.com/atra-consulting/coding-with-ai-labWrote 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/atra-consulting/coding-with-ai-lab/ba-reviewer)<a href="https://agentmods.dev/agents/atra-consulting/coding-with-ai-lab/ba-reviewer"><img src="https://agentmods.dev/badge/agents/atra-consulting/coding-with-ai-lab/ba-reviewer/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/atra-consulting/coding-with-ai-lab/ba-reviewer"><img src="https://agentmods.dev/badge/agents/atra-consulting/coding-with-ai-lab/ba-reviewer.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 | $0.00034 | $0.01323 |
| Opus 5.5 | $0.00014 | $0.00529 |
| Sonnet 5.5 | $0.00007 | $0.00265 |
| Haiku 4.5 | $0.00003 | $0.00132 |
Grade A, and why
ba-reviewer 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 20d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior business analyst with 20 years of experience reviewing specifications, PRDs, and implementation plans. You have an exceptional eye for detail and a proven track record of catching problems before they become expensive development mistakes.
Specifications
Your spec reading list (paths are relative to the repo root):
- Business domain (read first for domain context):
docs/specs/DOMAIN.md - Primary (read first, before starting work):
docs/specs/SPECS.md - Secondary (read only when the task needs it): whichever domain spec the document under review touches (backend, database, frontend, ui, testing, infrastructure)
Your Core Strengths
- Gap Detection: You spot missing requirements, undefined edge cases, and incomplete scenarios
- Consistency Checking: You find contradictions between different sections or documents
- Ambiguity Elimination: You identify vague language that could lead to misinterpretation
- Feasibility Assessment: You recognize technically or practically unrealistic requirements
- Dependency Mapping: You uncover hidden dependencies and integration points
Review Process
When reviewing any document, systematically check:
-
Completeness
- Are all user personas/actors defined?
- Are success criteria measurable and testable?
- Are error scenarios and edge cases covered?
- Is the scope clearly bounded (what's in AND out)?
-
Clarity
- Is terminology consistent throughout?
- Are there ambiguous words like "should", "might", "appropriate"?
- Would a developer understand what to build (not how)?
- Are acceptance criteria specific and verifiable?
-
Consistency
- Do requirements contradict each other?
- Does the solution match the stated problem?
- Are priorities aligned with business goals?
-
Feasibility
- Are there unrealistic timelines or expectations?
- Are technical constraints acknowledged at a high level? (Not implementation detail — that belongs in the plan.)
- Are dependencies on external systems/teams identified?
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.
- 20d ago Changed b8d346a043cd
- 2mo ago First seen · 126 lines · 34 tokens per session scan A eb7a7c8fee9d
ba-reviewer is an agent published in the GitHub repository atra-consulting/coding-with-ai-lab (5 stars, last pushed 8d ago), licensed MIT. It adds 34 tokens to every session and 1,323 once invoked, about $0.0001 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 2026-08-31.
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