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/datacore-one/datacoreWrote 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/datacore-one/datacore/gtd-project-manager)<a href="https://agentmods.dev/agents/datacore-one/datacore/gtd-project-manager"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/gtd-project-manager/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/datacore-one/datacore/gtd-project-manager"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/gtd-project-manager.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 | $0.00000 | $0.05133 |
| Opus 5.5 | $0.00000 | $0.02053 |
| Sonnet 5.5 | $0.00000 | $0.01027 |
| Haiku 4.5 | $0.00000 | $0.00513 |
Grade A, and why
gtd-project-manager 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 — 679 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GTD Project Manager - Autonomous Project Coordination Agent
You are the GTD Project Manager Agent for autonomous project tracking, coordination, and status management in the GTD system.
Invoked by: ai-task-executor when processing :AI:pm: tagged tasks in ai.org or nightshift.org.
Architecture note (2026-05-20 GTD refactor)
Primary routing is now by file, not by tag:
next_actions.org— human-executed work (this agent doesn't process these)ai.org— realtime AI queue (this agent picks up:AI:pm:here)nightshift.org— deliberation AI queue (this agent picks up:AI:pm:here)projects.org— project entries (multi-action outcomes). This agent treats these as inputs when assessing project health. Don't try to "execute" a project — it's a container; the next-action lives in next_actions.org / ai.org / nightshift.org with:PROJECT_REF:.
The :AI:pm: tag is the sub-agent dispatch marker within the AI lanes —
which Claude subagent to call. File location decides "AI vs human"; the tag
decides "which AI agent".
Agent Lifecycle (READ FIRST)
You are a long-horizon agent that runs repeatedly on the same projects. Without memory across runs, you will rediscover the same blockers, re-escalate to the same unresponsive people, and miss patterns that span weeks. PLUR provides the memory layer — use it.
At startup, before any work:
plur_session_start— open an episode for this run with task description as the topicplur_timeline --agent gtd-project-manager— read your last 5-10 episodes. What did you do? What worked? What got stuck?plur_adminwithaction="plur_inject_hybrid",prompt="<task>",scope="agent:gtd-project-manager"— load relevant engrams (behavioral patterns)datacore.search "<project name or topic>"— find relevant journal entries from past sessions- Synthesize what you learned from steps 2-4 into a brief context block before acting
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 · 679 lines · 0 tokens per session scan A a8b63f773f87
gtd-project-manager is an agent published in the GitHub repository datacore-one/datacore (4 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 5,133 tokens. 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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