Borrowing it
Nothing to install: this file belongs to anombyte93/prd-taskmaster. 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/anombyte93/prd-taskmaster/main/AGENTS.mdgit clone --depth 1 https://github.com/anombyte93/prd-taskmasterWrote 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/anombyte93/prd-taskmaster/agents-md)<a href="https://agentmods.dev/instructions/anombyte93/prd-taskmaster/agents-md"><img src="https://agentmods.dev/badge/instructions/anombyte93/prd-taskmaster/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/anombyte93/prd-taskmaster/agents-md"><img src="https://agentmods.dev/badge/instructions/anombyte93/prd-taskmaster/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 | $0.00732 | $0.00732 |
| Opus 5.5 | $0.00293 | $0.00293 |
| Sonnet 5.5 | $0.00146 | $0.00146 |
| Haiku 4.5 | $0.00073 | $0.00073 |
Grade A, and why
prd-taskmaster 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 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.
How it starts
The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Instructions — Atlas
Applies to ANY agent harness working in this repo (Codex, Gemini, Claude Code, or the next one). Claude Code also reads CLAUDE.md, which carries the same contract.
The end goal (north star — test every change against this)
Atlas's entry point is a frontier model acting as the driver. The driver understands the user's intent using skills built for it, then — inside a loop — decomposes the goal into optimal components and routes each to the cheapest capable executor, saving as many tokens as possible while delivering an outcome as good as if the frontier model had done all the work itself, at a fraction of the cost.
The executor pool is any CLI agent harness plus direct API paths, all in parallel — never a fixed provider list. Every feature decision is tested against: does this make the frontier-driver-decomposes-to-cheap-executors loop better, cheaper, or more provable?
The four moats (why this is a product, not a prompt pack):
- Cross-vendor arbitrage — route work across any harness/API by cost and capability.
- Engine-enforced unfakable gates — validate-tasks, ship-check (
SHIP_CHECK_OK), structural tests. A feature isn't a product feature until the engine enforces it. - Persistent vendor-neutral task graph — tasks.json survives across vendors/sessions.
- Cross-vendor cost ledger — telemetry + economy-report prove the savings.
Backend model (v4.1+)
TaskMaster is one optional pluggable backend. Backend resolution is
backend: auto|taskmaster|native in .atlas-ai/fleet.json; the 5-op protocol
(detect / init_project / parse_prd / expand / rate) lives in prd_taskmaster/backend.py.
- Task-state ops are engine-native ALWAYS:
python3 script.py next-taskandpython3 script.py set-status <id> <status>(MCP:next_task/set_task_status). Never call baretask-masteroutside a Mode-B-labeled block — structural tests enforce this. - No API keys → the backend returns a structured
agent_action_requiredpayload and YOU (the driving agent) do the generation, validated throughvalidate-tasksbefore any write. Never a crash. - The "## Backend operations" table in SKILL.md is normative. When docs and code disagree, fix the docs to match the table.
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 · 53 lines · 732 tokens per session scan A f6a65c20a07c
prd-taskmaster AGENTS.md is an instructions file published in the GitHub repository anombyte93/prd-taskmaster (607 stars, last pushed 2mo ago), licensed MIT. It adds 732 tokens to every session, about $0.0029 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 instructions, from other repositories
vscode buildNext.instructions.md
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next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).