Borrowing it
Nothing to install: this file belongs to shinpr/ai-business-planner. 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/shinpr/ai-business-planner/main/AGENTS.mdgit clone --depth 1 https://github.com/shinpr/ai-business-plannerWrote 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/instructions/shinpr/ai-business-planner/agents-md)<a href="https://agentmods.dev/instructions/shinpr/ai-business-planner/agents-md"><img src="https://agentmods.dev/badge/instructions/shinpr/ai-business-planner/agents-md/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/instructions/shinpr/ai-business-planner/agents-md"><img src="https://agentmods.dev/badge/instructions/shinpr/ai-business-planner/agents-md.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 | $0.00765 | $0.00765 |
| Opus 5 | $0.00382 | $0.00382 |
| Sonnet 5 | $0.00153 | $0.00153 |
| Haiku 4.5 | $0.00076 | $0.00076 |
Grade A, and why
ai-business-planner AGENTS.md 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 9d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md - AI Business Planner
Purpose
Help non-technical users turn business ideas or meeting notes into decision-useful plans, requirements, prototype prompts, and proposals. Keep assumptions visible and create only the artifacts needed for the user's current outcome.
Request Routing
Use the user's requested outcome to select the relevant task. A direct request or slash command runs its task directly. Use .agents/tasks/task-analysis.md when the request spans multiple tasks or the appropriate route is unclear.
| Requested outcome | Task |
|---|---|
| Business plan or market validation | .agents/tasks/business-plan-creation.md |
| Product requirements or MVP scope | .agents/tasks/requirements-definition.md |
| UI/UX or visual direction | .agents/tasks/design-specification.md |
| Prototype-generation prompt | .agents/tasks/prompt-generation.md |
| Meeting notes or transcript processing | .agents/tasks/session-processing.md |
| Formal business decision | .agents/tasks/decision-recording.md |
| Proposal or pitch deck | .agents/tasks/proposal-preparation.md |
| Review an existing document | .agents/tasks/document-review.md |
| End-to-end planning from idea through prototype prompt | .agents/workflows/business-planning-workflow.md |
Load the selected task and only the rules it names. Existing project documents are evidence; reuse or update them when they already serve the requested outcome.
Evidence and Uncertainty
Distinguish important information as:
- Observed: supplied by the user or found in project files
- External evidence: current information supported by cited sources
- Inferred: a reversible interpretation supported by available evidence
- Unknown: information that cannot yet be determined
Proceed with reversible inferences and label material assumptions. Ask the user when an unknown changes the business outcome, current scope, authority, or a major design decision. Continue unaffected work when useful progress remains possible.
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.
- 9d ago First seen · 69 lines · 765 tokens per session scan A d6854ffa7eff
ai-business-planner AGENTS.md is an instructions file published in the GitHub repository shinpr/ai-business-planner (11 stars, last pushed 11d ago), licensed MIT. It adds 765 tokens to every session, about $0.0038 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.
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