Pmm Okrs

pmm-okrs

A guided OKR builder for Product Marketing teams. Run it at the start of every quarter. Outputs a complete, review-ready OKR set you can paste directly into the PMM OKR Builder sheet. Learns from prior quarters to improve confidence calibration and KR quality. ---

Trigger

• When: Start of any quarter when setting PMM OKRs. When reviewing or stress-testing

existing KRs before committing. When building a measurement plan or leadership-ready exec narrative from a finalised OKR set.

• Not for: Company-level OKR design (not PMM-specific) → general planning tool.

Revenue forecasting or headcount planning. OKR tooling setup (Lattice, Workday) — this skill produces content, not configuration. If no quarterly strategy exists yet → run hs-pmm-strategy first, then return here.

• Example prompts:
• "Help me set our Q3 OKRs"
• "Are these KRs measurable enough?"
• "Build a scorecard for my chosen option"
• "Write OKRs for my team lead who owns competitive intelligence"
• "Stress-test this KR: improve win rate in enterprise"
• "I need to present our goals to the exec team next week"

---

Inputs

• Args: Company objective, PMM mandate, team size, primary metric, biggest challenge,

ICP, and named competitors. All optional at start — skill gathers via intake flow.

• Defaults: If no args provided, run intake flow via /build. If partial context

is provided, infer where possible and surface gaps explicitly before proceeding.

• Context keys:
• .agents/product-marketing-context.md — optional but recommended. Load Revenue

Levers, Goals & KPIs, Big Bet Campaigns, Company Overview silently if present.

• /context/meta-patterns.md — optional; recurring patterns from all skills (guardrail prompts)
• knowledge/okrs/rules.md — apply confirmed OKR craft rules by default.
• knowledge/okrs/hypotheses.md — test any active hypothesis if applicable today.
• decisions/ — check for prior decisions before making new recommendations.
• /context/skill-sessions.md — optional; prior quarter OKR data for confidence calibration

Brain contract: Reads: Section 2 (ICP), Section 3 (Positioning), Section 5 (Revenue), Section 6 (Goals). Writes: /context/skill-sessions.md, /foundation/brain.md Section 5 (if lever weights change). ---

Pre-flight

Load guardrails first: Check /context/meta-patterns.md for recurring OKR patterns. If pattern matches (e.g., "confidence calibration off by 15% in Q2-Q3"), surface guardrail prompt before Step 1.

Before starting, check .agents/product-marketing-context.md. If it exists — load silently:

• ## Revenue Levers → align OKRs to the stack-ranked levers
• ## Goals & KPIs → use North Star + OMTM as anchors
• ## Big Bet Campaigns → surface as project goals
• ## Company Overview → stage and business model context

Confidence awareness: If loaded sections are 🔴, flag before building OKRs: > "Revenue Levers is marked as Placeholder — OKRs built on this may need revisiting. Want to update it first?" If missing: Proceed. Surface once: > "Run hs-product-marketing-context BUILD first for sharper OKRs. Continuing."

Load prior quarter data: Check /context/skill-sessions.md for last quarter's OKR results to calibrate confidence: > "Last quarter: confidence was 75%, actual achievement was 78%. You're well-calibrated. Recommend similar range this quarter."

Related skills — cross-reference before or after this skill:

• hs-pmm-strategy → run before this skill if no quarterly strategy exists yet
• hs-product-requirement-doc → PRDs inform project OKRs; check for alignment
• hs-gaccs-brief → campaign briefs should trace back to OKR project goals
• meta-synthesis → after 3+ quarters logged, meta-synthesis detects OKR patterns

---

Steps

Step 0: Surface Guardrails (NEW)

Before intake, check for patterns:

If /context/meta-patterns.md exists and contains OKR patterns:

🔁 PATTERN DETECTED FROM PRIOR QUARTERS

I've detected [specific pattern] in [N] prior quarters.
Example: "Confidence off by 15%", "External dependency blockers 3+ times", "KR design failure on 'improve adoption'"

Quick question: Are you seeing this pattern again in Q4?
- If YES → we'll flag it as a confirmed problem + propose a fix
- If NO → we'll watch for other patterns

This helps calibrate your confidence and KR design.

Common guardrail patterns to surface:

• "Confidence too high (90%+) but achievement 65%" → "Recommend: set confidence 70% or below"
• "External dependencies blocked 3+ KRs" → "Build dependency risk into confidence"
• "KR too vague again ('improve adoption')" → "Be specific: 'Adoption in SMB segment 60% → 75%'"
• "Lever weight assumptions changed mid-quarter" → "Lock lever weights at start"

If patterns apply, ask guardrail question. User can skip, but they've been warned.

Step 1 — /build

1. Run intake (or infer from pasted context).
2. Load knowledge/okrs/rules.md + check guardrails from /context/meta-patterns.md.
3. Check decisions/ for prior choices in this area.
4. Check /context/skill-sessions.md for prior quarter confidence calibration.
5. Generate three OKR options.
6. Run independent evaluation pass (Block 3) on all three.
7. Present with Quality Gate results inline + confidence recommendations based on prior quarters.
8. Log option selection to decisions/.

Step 2 — /review

1. Accept pasted OKRs.
2. Run each KR through all five Quality Gates (binary).
3. Flag every failure with an ADVERSARIAL CALLOUT and a rewrite.
4. Return annotated set.

Step 3 — /scorecard

1. Work from OKRs in session or ask user to paste.
2. Map each KR to metric, target, measurement method.
3. Group by category.
4. Confirm Weight = 100%.
5. Output scorecard.

Step 4 — /exec

1. Confirm OKRs are finalised (not drafts).
2. Translate to one-paragraph exec narrative.

Step 5 — /map

1. For each KR, generate required projects with owner type, effort (S/M/L), timeline.
2. Flag capacity conflicts if team size known.
3. Cross-reference against guardrails: "External dependencies flagged in 3 prior quarters. This KR has 2. Accept risk?"

Step 6 — /stress-test [KR]

1. Accept one KR.
2. Run through five Quality Gates.
3. Return per-gate pass/fail + rewrite.

Step 7: Post-Session Logging (NEW)

After every session, log structured data to /context/skill-sessions.md:

skill: pmm-okrs
session_date: 2026-06-21
quarter: "Q3 2026"
okr_set_version: 1
objectives_count: 3
key_results_count: 9
confidence_level: "medium"
confidence_range: "65-70%"
krs_with_baseline_metrics: 9
krs_with_tracking_mechanism: 7
krs_with_stretch_factor: 6
aggressive_vs_conservative: "mixed"
dependencies_identified: true
dependencies_external: 3
dependencies_internal: 1
prior_quarter_okrs:
  - quarter: "Q2 2026"
    krs_achieved: 7
    krs_partial: 1
    krs_missed: 1
    achievement_rate: 0.78
    confidence_predicted: 0.75
current_vs_prior_stretch: "more_aggressive"
confidence_vs_last_quarter: "higher"
confidence_calibration_delta: "+2%"
output_path: "/foundation/okrs/Q3-2026-PMM-OKRs.md"
guardrails_triggered:
  - "External dependencies: 3 (same as Q2). Last quarter we missed 1 KR due to external dependency. Recommend: align with dependent teams by Week 1 of Q3."
  - "Stretch factor: 6/9 KRs are ambitious (2x+). This is higher than Q2 (4/8). Recommend: ensure team capacity supports this."
  - "Confidence calibration: Q2 predicted 75%, achieved 78%. You're well-calibrated. Recommend similar range (72-78%) for Q3."
brain_updates_proposed: []

This feeds into meta-synthesis skill (monthly) which detects OKR patterns across quarters and updates guardrails.

Step 8: Deliver Output and Log Learning

Deliver the OKR set. Then run the self-improvement loop: write session file → update knowledge base → log decisions → run quality gate → propose confidence adjustments. ---

Outputs

• Files written:
• /context/skill-sessions.md — row appended with session metadata and guardrails (NEW)
• decisions/YYYY-MM-DD-{topic}.md when a strategic OKR choice is logged.
• knowledge/okrs/hypotheses.md and rules.md when the self-improvement loop triggers at session end.

• Chat output format: Three OKR option blocks in code-fence structured output,

each with Quality Gate results inline. Scorecard table. Exec Summary paragraph. All formatted for direct paste into the PMM OKR Builder spreadsheet.

• External side effects: None beyond context writes.

---

Verification

• Guardrails checked before intake (Step 0) — patterns from prior quarters surfaced.
• All /build output contains three OKR options unless user explicitly requests fewer.
• Every option includes Quality Gate results (five binary checks) before delivery.
• No output delivered before the independent evaluation pass (Block 3) has run.
• Adversarial callouts surface inline before delivery, never post-delivery.
• Decision log written whenever a recommendation will affect the user's quarter.
• /exec output produced only from finalised OKRs, not from draft options.
• Scorecard Weight confirmed at 100% before delivery.
• Confidence calibration checked against /context/skill-sessions.md prior quarter data.
• Session logged to /context/skill-sessions.md with all metadata.

---

Do Not Use For

• hs-pmm-strategy — if no quarterly strategy exists yet, run that first. This skill

builds OKRs from a strategy, not instead of one.

• hs-prioritization-frameworks — for prioritising which initiatives to include in

a quarter before OKRs are set. Run that upstream, then return here.

• hs-gaccs-brief — for campaign planning that traces back to OKRs already set.

Use after /build to brief individual campaigns.

• Company-level OKR design — this skill is PMM-specific. Exec team or company

OKRs require different framing and are out of scope.

• OKR tooling setup — this skill produces OKR content, not Lattice/Workday

configuration or workflow automation. ---

Reasoning Architecture

Block 1 — Knowledge Architecture (Learning Loop)

Before any task:

1. Load knowledge/INDEX.md and relevant domain folders.
2. Apply rules.md by default.
3. Test any active hypothesis if applicable today.
4. Load /context/meta-patterns.md for cross-skill guardrails.
5. Load /context/skill-sessions.md for prior quarter confidence calibration.

After any session:

1. Extract 1–3 insights.
2. Unconfirmed → hypotheses.md.
3. Confirmed 3+ times → auto-promote to rules.md.
4. Contradicted → demote to hypotheses.md.
5. Log confidence calibration delta for future quarters.

> Environment note: Persistent /knowledge/ works in Claude Code and Cowork. > In Claude.ai chat, surface insights at end of session for manual carry-forward.

Block 2 — Decision Journal

Check decisions/ before any recommendation. Log new decisions immediately.

File: decisions/YYYY-MM-DD-{topic}.md
Decision / Context / Alternatives / Reasoning / Trade-offs / Supersedes

Log when:

• Choosing between OKR options.
• Recommending a measurement method.
• Flagging a failing gate.
• Any recommendation affecting the user's quarter.
• Confidence calibration adjustments based on prior quarter data.

Block 3 — Independent Evaluation Pass

After generating any output: re-read cold as evaluator. Run all five Quality Gates binary. Rewrite failures before delivery. Report gate results inline.

Confidence calibration check: Compare predicted confidence vs. actual achievement from prior quarter. Adjust recommendations:

Last quarter: Predicted 75%, Achieved 78% → You're well-calibrated
This quarter: Recommend 72-78% confidence range

---

Commands

/build

Builds three OKR options from scratch with Quality Gate results and confidence calibration. Example prompts:

• Help me set our Q3 OKRs. 3-person PMM team, B2B SaaS, company OKR: grow ARR 40%.
• Build OKRs for a solo PMM at a Series B. Challenge: positioning isn't landing.

/review

Audits existing OKRs against all five Quality Gates. Returns exact fixes. Example input:

Objective: Improve go-to-market in mid-market.
KR 1: Launch 4 battlecards. KR 2: Run monthly training. KR 3: Increase pipeline.

/scorecard

Maps each KR to metrics, targets, and measurement methods.

/exec

Generates one-paragraph exec-ready OKR narrative for QBRs and VP presentations.

/map

Builds OKR → Projects table with owner type, effort (S/M/L), and timeline. Cross-references guardrails.

/individual [specialty]

Generates OKRs for an individual PMM contributor.

• /individual positioning · /individual competitive · /individual gtm

/stress-test [KR]

Runs one KR through all five Quality Gates. Returns pass/fail + rewrite. ---

Output Format

═══════════════════════════════════════════
OPTION [A / B / C] — [Strategic Focus]
═══════════════════════════════════════════
OBJECTIVE: [1–2 sentence qualitative goal.]
KR 1 — [Name]: [Outcome. Target. Deadline. Measurement.]
KR 2 — [Name]: [Outcome. Target. Deadline. Measurement.]
KR 3 — [Name]: [Outcome. Target. Deadline. Measurement.]
CONFIDENCE: [X%]
CONFIDENCE REASONING: [Based on prior quarter calibration: if last quarter predicted 75% achieved 78%, recommend similar range]
CHOOSE THIS WHEN: [1-sentence fit description.]
KEY PROJECTS: 1. [name — KR] 2. [name — KR] 3. [name — KR]
QUALITY GATE RESULTS:
Gate 1 — Outcome not output:           ✅ / ❌
Gate 2 — Measurable without ambiguity: ✅ / ❌
Gate 3 — Causally linked to objective: ✅ / ❌
Gate 4 — 60–70% confidence:            ✅ / ❌
Gate 5 — Three or fewer KRs:           ✅ / ❌
GUARDRAILS: [Cross-skill patterns from prior quarters, if any]
═══════════════════════════════════════════

---

Quality Gates

| Gate | Test | Fail | Pass | |---|---|---|---| | 1 | Outcome, not output | "Launch 4 battlecards" | "Win rate up 8%" | | 2 | Measurable without ambiguity | "Improve messaging" | "80% resonance from 50 reviews" | | 3 | Causally linked to objective | PMM doesn't own lever | PMM controls what moves this | | 4 | 60–70% confidence | >90% or ⚠️ ADVERSARIAL CALLOUT: [Issue] — [Why it's a problem and what to write instead.] ---

Operating Rules

• Guardrails first. Load /context/meta-patterns.md at pre-flight. Surface guardrail prompt if pattern matches this quarter's planning.
• Load brain context before intake. Pre-flight runs silently — never ask for context already loaded.
• Load prior quarter data for confidence calibration. Check /context/skill-sessions.md before confidence recommendations.
• Three options minimum on /build. Choice architecture is the value.
• Independent evaluation pass is non-negotiable. Unreviewed output is not delivered.
• Adversarial callouts surface before delivery, not after. Rewrites happen during generation.
• Decision logging is not optional. Every recommendation affecting the quarter gets logged.
• Writes only to decisions/, knowledge/, and /context/skill-sessions.md. No writes to brain file.
• Confidence range is enforced. >90% or <50% triggers an adversarial callout. Calibrate against prior quarter achievement.
• Gate results in table format only. Binary ✅ / ❌ — no narrative substitution.
• Scorecard Weight confirmed at 100% before delivery. Surface discrepancy if unbalanced.
• /exec only from finalised OKRs. Prompt for option choice if drafts only.
• Always log. Every quarter's OKR session logged to /context/skill-sessions.md. Meta-synthesis learns from achievement rates across quarters.

---

Quality Gate

Runs before final delivery. Score each criterion 1–3. Minimum 17/21 to pass. | Criterion | Standard | Score (1–3) | |---|---|---| | Guardrails surfaced | /context/meta-patterns.md checked at pre-flight | | | Confidence calibration | Prior quarter data checked for adjustment recommendations | | | Three option

…

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: stefanoskarakasis
• Source: stefanoskarakasis/Product-Marketing-Skills
• License: MIT
• Homepage: https://stefanoskarakasis.substack.com/

Install and usage instructions live in the source repository linked above.