plan-okrs

plan-okrs is a command for Claude Code from phuryn/pm-skills. It costs 17 tokens per session (870 once invoked), scanned A, original, MIT.

An OKR planning assistant that creates team objectives and measurable key results aligned with company goals. OKRs, or Objectives and Key Results, pair a qualitative goal with specific results that show whether it is being achieved.

In plain words
What is it for?
Use it to brainstorm quarterly or custom-period OKRs from company objectives, strategy documents, past results, and team constraints.
Why use it?
It helps turn broad company strategy into clear team priorities and measurable outcomes. It also balances early activity measures with later results and assigns owners when the information is available.

Command for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Part of the pm-execution plugin — 16 skills, 11 commands shipped together

Good fit Use it to brainstorm quarterly or custom-period OKRs from company objectives, strategy documents, past results, and team constraints.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/phuryn/pm-skills/plan-okrs
About the project

phuryn/pm-skills is a marketplace of reusable skills, commands, and plugins that guide AI assistants through product-management work such as discovery, strategy, planning, metrics, launches, and growth. It is for product managers and teams using Claude Code, Cowork, or compatible assistants. The catalogue entries are the project's own workflows and extensions.

phuryn/pm-skills · 26,066 stars · on GitHub · productcompass.pm

Install

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.

Clone the repo
git clone --depth 1 https://github.com/phuryn/pm-skills

Made for: Claude Code.

Or install pm-execution, the plugin that ships this one along with the rest of its 16 skills, 11 commands.

Wrote 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.

agentmods badge for plan-okrs

README.md
[![agentmods](https://agentmods.dev/badge/commands/phuryn/pm-skills/plan-okrs.svg)](https://agentmods.dev/commands/phuryn/pm-skills/plan-okrs)
Your own site
<a href="https://agentmods.dev/commands/phuryn/pm-skills/plan-okrs"><img src="https://agentmods.dev/badge/commands/phuryn/pm-skills/plan-okrs.svg" alt="Measured on agentmods" height="20"></a>
Per session 17 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 870 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00017 $0.00870
Opus 5 $0.00009 $0.00435
Sonnet 5 $0.00003 $0.00174
Haiku 4.5 $0.00002 $0.00087

Measured 8d ago against content hash 64fa936f4d2c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

plan-okrs 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 8d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • plan-okrs — 100% identical, 0 lines differ
pm-execution/commands/plan-okrs.md · 99 lines

How it starts

The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/plan-okrs -- Team OKR Planning

Generate well-structured OKRs that connect team work to company strategy. Produces 3 OKR sets with qualitative objectives and quantitative key results.

Invocation

/plan-okrs Growth team Q2 — company goal is 50% ARR increase
/plan-okrs Onboarding squad aligned to "improve activation rate"
/plan-okrs [upload company OKRs or strategy doc]

Workflow

Step 1: Gather Context

Ask the user:

  • What team or product area are these OKRs for?
  • What time period? (quarterly is standard, but could be annual or custom)
  • What are the company-level objectives these should ladder up to?
  • What happened last quarter? (hits, misses, learnings)
  • Any constraints or known priorities?

Accept company OKRs or strategy documents as uploads.

Step 2: Generate OKRs

Apply the brainstorm-okrs skill:

  • Create 3 OKR sets (Objective + 3-5 Key Results each)
  • Objectives: Qualitative, inspiring, ambitious but achievable, action-oriented
  • Key Results: Quantitative, measurable, time-bound, have clear owners
  • Ensure OKRs ladder to company objectives with visible connection
  • Balance leading indicators (activity) with lagging indicators (outcomes)

Step 3: Validate Quality

Check each OKR against best practices:

  • Is the Objective inspiring? (Would you rally a team around it?)
  • Are Key Results measurable? (Can you check completion with data, not judgment?)
  • Are targets ambitious but not demoralizing? (70% achievement = well-calibrated)
  • Are there 3-5 KRs per Objective? (More = unfocused)
  • Do KRs avoid gaming? (e.g., "ship 5 features" incentivizes shipping junk)

Flag any issues and suggest improvements.

Step 4: Present and Iterate

## Team OKRs: [Team Name] — [Period]

**Aligned to**: [Company Objective(s)]

### Objective 1: [Inspiring qualitative statement]
| # | Key Result | Baseline | Target | Owner |
|---|-----------|----------|--------|-------|
| KR1 | [measurable result] | [current] | [target] | [team/person] |
| KR2 | ... | ... | ... | ... |
| KR3 | ... | ... | ... | ... |

### Objective 2: [Inspiring qualitative statement]
[same format]

### Objective 3: [Inspiring qualitative statement]
[same format]

### Alignment Map
Company Objective → Team Objective → Key Results → Expected Impact

### Scoring Guide
- 0.0-0.3: Significant miss — investigate and learn
- 0.4-0.6: Progress made but fell short
- 0.7-0.9: Well-calibrated stretch goal — this is the target zone
- 1.0: Either nailed it or target wasn't ambitious enough

### Check-in Cadence
- **Weekly**: Quick traffic-light update on each KR
- **Mid-quarter**: Deep review, adjust targets if context changed
- **End of quarter**: Score, reflect, feed into next quarter

Read the full file on GitHub · 99 lines

Changes

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.

  1. 8d ago First seen · 99 lines · 17 tokens per session scan A 64fa936f4d2c

Subscribe to this mod's changes

plan-okrs is a command published in the GitHub repository phuryn/pm-skills (26,066 stars, last pushed 2mo ago), licensed MIT. It adds 17 tokens to every session and 870 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 2026-08-30.