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.
npx skills add h4vzz/awesome-ai-agent-skills --skill project-managementgit clone --depth 1 https://github.com/h4vzz/awesome-ai-agent-skillsWrote 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/skills/h4vzz/awesome-ai-agent-skills/project-management)<a href="https://agentmods.dev/skills/h4vzz/awesome-ai-agent-skills/project-management"><img src="https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/project-management/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/skills/h4vzz/awesome-ai-agent-skills/project-management"><img src="https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/project-management.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 | $0.00044 | $0.02417 |
| Opus 5.5 | $0.00018 | $0.00967 |
| Sonnet 5.5 | $0.00009 | $0.00483 |
| Haiku 4.5 | $0.00004 | $0.00242 |
Grade A, and why
Project Management 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.
This is a copy
100% identical to project-management — 4 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 — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Management
This skill enables an AI agent to serve as a project management co-pilot for software teams. It covers the full lifecycle: breaking high-level goals into actionable tasks with acceptance criteria, estimating effort in story points, organizing work into sprints or Kanban boards, tracking progress with burndown data, identifying blockers and risks, and generating stakeholder-ready status reports. The agent integrates with Jira, Linear, GitHub Issues, and Trello so that all changes are reflected in the team's actual project tracker.
Workflow
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Gather Project Context Collect the project name, team roster (with roles and capacity), high-level goals, key deadlines, and the preferred methodology (Scrum, Kanban, or a hybrid). If a project tracker is already in use, connect to its API and import the current backlog, labels, and sprint configuration so the agent starts from the existing state rather than a blank slate.
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Decompose Work into Tasks Break each high-level goal into epics, then into user stories, and finally into sub-tasks small enough to complete in one to two days. Write each user story in the standard format: "As a [role], I want [capability] so that [benefit]." Attach acceptance criteria as a checklist on every story. Identify dependencies between tasks and flag any that form a critical path. Assign story-point estimates using the Fibonacci scale (1, 2, 3, 5, 8, 13) based on complexity, uncertainty, and effort.
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Plan Sprints or Populate the Board For Scrum teams, create a sprint with a start date, end date, and sprint goal. Pull stories from the top of the prioritized backlog until the team's velocity (historical average story points per sprint) is reached. For Kanban teams, enforce work-in-progress (WIP) limits per column and ensure the board columns match the team's workflow (e.g., Backlog → In Progress → Review → Done). Push the plan to the connected project tracker via its API.
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Track Progress and Surface Blockers Poll the project tracker on a configurable interval (default: daily). Calculate burndown and cumulative-flow metrics. Detect when a task has been "In Progress" longer than its estimate and flag it as at risk. Identify dependency chains where a blocked upstream task is stalling downstream work. Post a daily digest to the team's Slack or Teams channel summarizing completed items, in-progress items, and blockers.
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 · 161 lines · 44 tokens per session scan A 3b6290245333
Project Management is a skill published in the GitHub repository h4vzz/awesome-ai-agent-skills (36 stars, last pushed 22d ago), licensed MIT. It adds 44 tokens to every session and 2,417 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to project-management, differing in 4 lines, and is treated as a copy.
Other skills, from other repositories
jira-cli
Interact with Jira from the command line to create, list, view, edit, and transition issues, manage sprints and epics, and perform common Jira workflows. Use when the user asks about Jira tasks, tickets, issues, sprints, or needs to manage project work items.
run-task
Execute a single Todo task through In Progress to Review, meeting every acceptance criterion with tests and vibe-lint checks. Refuses Planning-status tasks. Invoked as /agiflow:run-task . Uses gettask, updatetask, createtaskcomment.
blueprint
Turn a one-line objective into a step-by-step construction plan for multi-session, multi-agent engineering projects. Each step has a self-contained context brief so a fresh agent can execute it cold. Includes adversarial review gate, dependency graph, parallel step detection, anti-pattern catalog, and plan mutation…
agent-phase-closeout
A Chinese-language process for closing out a completed work stage and recording its state. It summarizes finished work, preserves decisions, freezes completed interfaces, and writes a resume checkpoint.
orchestrate
Pipeline orchestration: dispatch the highest-priority ready tasks/work units to agents, manage capacity, and coordinate the Todo to Done flow. Invoked as /agiflow:orchestrate. Uses listtasks, listactivetasksbyorg, listmembers, updatetask, getworkunitprogress.
google-workspace-ops
Operate across Google Drive, Docs, Sheets, and Slides as one workflow surface for plans, trackers, decks, and shared documents. Use when the user needs to find, summarize, edit, migrate, or clean up Google Workspace assets without dropping to raw tool calls.