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 hardiktiwari/PM-operating-OS --skill stakeholder-updategit clone --depth 1 https://github.com/hardiktiwari/PM-operating-OSWrote 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/hardiktiwari/pm-operating-os/stakeholder-update)<a href="https://agentmods.dev/skills/hardiktiwari/pm-operating-os/stakeholder-update"><img src="https://agentmods.dev/badge/skills/hardiktiwari/pm-operating-os/stakeholder-update/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/hardiktiwari/pm-operating-os/stakeholder-update"><img src="https://agentmods.dev/badge/skills/hardiktiwari/pm-operating-os/stakeholder-update.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 | $0.00028 | $0.00476 |
| Opus 5 | $0.00014 | $0.00238 |
| Sonnet 5 | $0.00006 | $0.00095 |
| Haiku 4.5 | $0.00003 | $0.00048 |
Grade A, and why
stakeholder-update 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 10d 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.
What it actually says
Stakeholder Update
Help PMs write concise status updates for leadership and stakeholders. Produces scannable, metric-driven summaries that keep everyone informed without overwhelming.
When to Use
- Weekly or bi-weekly status updates
- Milestone or phase completion reports
- Progress summaries for leadership
- Cross-team or cross-org updates
- When asked "send an update to [stakeholder]"
Process / Template
1. Identify Audience and Cadence
- Who is the audience? (leadership, peers, cross-functional)
- How often? (weekly, bi-weekly, ad hoc)
- What do they care about? (metrics, risks, decisions)
2. Gather Content
- Progress since last update
- Key metrics (current vs. target)
- Wins and milestones
- Risks and blockers
- Decisions needed
- Next period focus
3. Structure the Update
TL;DR
- One sentence: on track / at risk / behind, plus headline
Progress
- 3–5 bullets: what shipped, what advanced, what's in progress
- Tie to goals or milestones where possible
Metrics
- Key numbers (current vs. target or prior period)
- Trend direction (↑ ↓ →)
Risks / Blockers
- What could derail
- What you need (decision, resource, escalation)
Next Up
- Top 2–3 priorities for the coming period
Asks
- Explicit: what you need from the reader
4. Apply Principles
- Lead with the headline — don't bury the lead
- Be specific — numbers, dates, names
- Keep it scannable — bullets, headers, white space
- Anticipate questions — address likely concerns
- End with clarity — what's next, what's needed
Output
A Stakeholder Update that:
- Can be read in under 2 minutes
- Clearly signals status (green/yellow/red)
- Highlights metrics and progress
- Makes asks explicit
- Is ready for email, Slack, or a shared doc
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.
- 10d ago First seen · 74 lines · 28 tokens per session scan A 91aec90dc1b3
stakeholder-update is a skill published in the GitHub repository hardiktiwari/PM-operating-OS (5 stars, last pushed 4mo ago), licensed MIT. It adds 28 tokens to every session and 476 once invoked, about $0.0001 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
bcc-throughline
BCC global progress cockpit (plans.md/progress.md/findings.md). Slash: /bcc-throughline · chat: bcc:throughline · "where are we" · reprioritize · resume after /clear. Not for coding or full PLAN grill.
handoff
Guides the Claude Code agent through completing a task, selecting a handoff tier, building a valid completion-card, and performing a clean task handoff.
execute-plan
Implement a written plan (from write-plan or interview-plan) when the user says execute or implement it. Loads the plan, executes ready tasks in waves in the ticket venue, runs the plan's review gate itself. Do not use while still interviewing or writing the plan.
generate-stories
Translate a single Epic into clear, actionable User Stories with explicit acceptance criteria. Activate when an Epic is defined and work needs to be prepared for Delivery execution.
review-input
Adversarial review of any input (human idea, agent analysis, research report, feedback, observation) BEFORE it mutates persistent project state. Universal interceptor with domain auto-detection, 2-phase classification + evaluation, and triple-verdict output (veracity / fit / actionability). Anti-girouette guardrail…
review-story-alignment
Adversarial review of generated stories against the Discovery Session Brief, referenced DECs, and Epic DoR. Detects contradictions, omissions, and intent drift BEFORE stories reach Delivery. Produces a structured verdict (PASS/FAIL) with specific findings per story. Triggers after generate-stories, before backlog…