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 agentmods add skills/getappz/agentflare/pmnpx skills add getappz/agentflare --skill pmgit clone --depth 1 https://github.com/getappz/agentflareWrote 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/getappz/agentflare/pm)<a href="https://agentmods.dev/skills/getappz/agentflare/pm"><img src="https://agentmods.dev/badge/skills/getappz/agentflare/pm.svg" alt="Measured on agentmods" 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 | $0.00085 | $0.03340 |
| Opus 5 | $0.00043 | $0.01670 |
| Sonnet 5 | $0.00017 | $0.00668 |
| Haiku 4.5 | $0.00009 | $0.00334 |
Grade A, and why
pm 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 3d 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 — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM Agent — product management over agentflare items
Two arms, one contract boundary
- Reporting (default, Part 1 below):
/pm:standup,/pm:groom,/pm:plan,/pm:health,/pm:portfolio— always read-only, never mutate. - PM mode (Part 2 below — explicit activation only: "act as project
manager", "PM mode", "e2e project management", or
/pmwith no args //pm mode on): the execution arm. Creates items, hands work off to real agents, never implements inline. Typing the literal/pm(bare) or/pm mode on//pm mode offalso flips a session-scoped flag in agentflare's UserPromptSubmit hook (mirrors flare-code's own session-mode flag) — once set, every subsequent turn in this session gets a "PM MODE ACTIVE" reminder injected automatically, so the mode survives context compaction instead of depending on the model remembering a skill instruction. Only/pm mode offclears it; it does not expire on its own.
Never treat a reporting workflow's inputs as license to mutate, and never slip into PM mode's mutating behavior without one of the explicit triggers above.
Scope
Default: one project — whichever project the current repo resolves to.
/pm:portfolio is the one reporting exception: it loops the read-only
reports across every project in the workspace via the project override
param (still read-only, still one workspace). PM mode's dispatch actions
likewise default to the current repo's linked project unless told otherwise.
Part 1 — Reporting workflows (read-only, non-negotiable)
Never call item with any of: create, update, update_state, delete, claim,
heartbeat, release, done, cancel, add_label, remove_label — nor comment
create/edit/delete. Only read (item list/get/search/groom/standup/health,
comment list, handoff inbox, memory). Output is suggestions for a
human, never actions taken.
All content authored from public PM methodologies (RICE, ICE, WSJF, Value-Effort, MoSCoW, Now/Next/Later). No third-party notices required.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 240 lines · 85 tokens per session scan A 0d94a47e62cb
pm is a skill published in the GitHub repository getappz/agentflare (2 stars, last pushed 3d ago), licensed Apache-2.0. It adds 85 tokens to every session and 3,340 once invoked, about $0.0004 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 2026-08-31.
Other skills, from other repositories
task-loop
任务目标驱动执行闭环预装 skill,整合任务识别/规划/派发搜推/验收/BBS 接力/arch 场景规划变体(planning-arch)与架构师名册 mock(arch-analysis)共七段为单一 skill,预装到所有 bot 等同各段单独安装到对应 bot;各段按各自触发词自门控仅命中段执行(用户面 /task 或 [RESUMETASK] 或副屏标签命中识别;框架 [planning] 命中规划,arch 场景含「某某某公司」命中 planning-arch 变体;框架 [search] 命中派发搜推;worker 叶子自验收命中验收;引擎 BBS 通知命中接力,其 scoped 叶子 instruction…
bcs-coordination
全场景多智能体协同和交互引擎。覆盖多Bot复杂任务协同与沉浸式娱乐互动。通过提供注册发现、群组构建、上下文融合及路由通信能力等核心能力，支持能力互补、信息和知识的融合、冲突消解、工作流编排，以及2C场景下多人游戏互动等。.
bbs-relay-pickup
被唤醒时从 task API 发现 BBS 升级任务、CAS 占根、自判剩余、挂节点、执行、经回投写回.
bcs-coordination
全场景多智能体协作和交互引擎。覆盖 Bot 注册发现、自由聊天、任务协作、上下文融合、路由通信和自定义协作。用户需要自定义参与角色、执行步骤、串并行关系或最终交付物时，使用自定义协作能力，并通过 BCS 的 statemachine YAML 实现和校验。.
task-planning-arch
计算任务 gap 并产出下一步可执行子任务 List[TaskSpec];gap 已闭返回空数组。对齐 arch 场景(架构师名册/技术栈概览/双视角分析)确定式分解——按根目标交付物集合 + donechildren 查表(参照 task-planning storage 特例,非自由 LLM 分解)。.
task-search
在框架预查的候选 bot 集里决出执行者(who)与协作方式(how),返回 4 态 SearchResult(HITSINGLE/HITGROUP/HITMULTIBOTS/MISS)。对齐案例剧本确定式映射。.