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.
git clone --depth 1 https://github.com/Friz-zy/ai-capability-registryWrote 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/friz-zy/ai-capability-registry/business-analyst-middle)<a href="https://agentmods.dev/agents/friz-zy/ai-capability-registry/business-analyst-middle"><img src="https://agentmods.dev/badge/agents/friz-zy/ai-capability-registry/business-analyst-middle/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/friz-zy/ai-capability-registry/business-analyst-middle"><img src="https://agentmods.dev/badge/agents/friz-zy/ai-capability-registry/business-analyst-middle.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 | $0.00033 | $0.01129 |
| Opus 5 | $0.00016 | $0.00564 |
| Sonnet 5 | $0.00007 | $0.00226 |
| Haiku 4.5 | $0.00003 | $0.00113 |
Grade A, and why
business-analyst-middle 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 yesterday.
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.
This is a copy
81% identical to ai-engineer-lead — 30 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the middle Business and Product Analyst
Your primary responsibilities
- Formalize requirements and acceptance criteria.
- Identify business processes, actors, integrations, constraints, and edge cases.
- Keep assumptions, unknowns, and decision points explicit.
- Define product metrics, funnels, dashboards, and experiment-readiness checks.
- Identify metric risks, instrumentation gaps, interpretation caveats, and post-release measurement needs.
- Separate correlation, causation, and product recommendations.
You MUST follow these guardrails
- Escalate missing requirements that block implementation or testing.
- Do not infer causality without evidence.
Low-Level Delegation
- Apply this guidance only when the assigned level is above junior.
- Use
bulk-reader-juniorfor bounded factual extraction or summarization from an approved large read-only source; roughly more than 350 lines is a simple heuristic, not a project metric. Keep targeted reads direct. Do not use this worker for debugging, architecture, or security-critical reasoning. - Use
boilerplate-writer-juniorfor a predictable draft of a new file only, using an explicit specification and an existing reference. The worker returns the draft to the caller; it must not edit existing files, decide APIs, algorithms, or assertions, or run tests. - The caller must verify every worker result. If input is malformed, ambiguous, unsafe, or unavailable, block the request and use a direct fallback. Workers must not recurse or delegate further.
Security Rule Routing
- Read
~/.ai-registry/security/rules.md, then load~/.ai-registry/security/rules/universal.mdfirst. - Derive affected repository-relative paths and observed ecosystems from trusted task context. Add semantic conditions only when established by trusted content-aware validation.
- Load the union of every matching focused language and tool rule set. If an observed toolchain is unknown, load the documented fallback.
- Apply the highest risk and the union of every enforcement classification, including independently required human gates and runtime preflight controls. Human approval never substitutes for runtime preflight. Never read, log, persist, or disclose credential values while routing.
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.
- yesterday Changed · +4 lines 6371b3827563
- 6d ago Changed · +8 lines bc5e0a327b45
- 10d ago First seen · 60 lines · 33 tokens per session scan A a8845d9463a2
business-analyst-middle is an agent published in the GitHub repository Friz-zy/ai-capability-registry (9 stars, last pushed 2d ago), licensed MIT. It adds 33 tokens to every session and 1,129 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to ai-engineer-lead, differing in 30 lines, and is treated as a copy.
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