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OKR Planning Skill · a5c-ai | DecimalAI

a5c-ai/OKR Planning

SkillScore82Maintained

Objectives and Key Results planning, tracking, and alignment capabilities

productivityby a5c-ai

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

Product Management pack

1 · One-time — install the CLI (docs ↗)

pip install decimalai

2 · Get the skill — writes .claude/skills/a5c-ai-okr-planning/SKILL.md

decimalai skills pull a5c-ai-okr-planning --out .claude/skills/

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/a5c-ai-okr-planning/SKILL.md https://app.decimal.ai/s/a5c-ai-okr-planning/SKILL.md

Raw file: /s/a5c-ai-okr-planning/SKILL.md ↗ · machine-readable summary at /s/a5c-ai-okr-planning.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

No production data for this skill yet — usage numbers appear here once agents start running it.

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

22 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 26d ago

Yes — +41% lift · at higher cost+76% tokens0% turns82% of whole cases pass with skill (18/22)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-07	✗→✓	▲ Improved	73%	0%
case-08	✗→✓	▲ Improved	38%	0%
case-09	✗→✓	▲ Improved	100%	0%
case-10	✗→✓	▲ Improved	130%	0%
case-11	✗→✓	▲ Improved	110%	0%

Showing 5 of 22 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/10/2026

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

a5c-ai / babysitter

library/specializations/product-management/skills/okr-planning/SKILL.md

View on GitHub ↗

License MITImported 8/10/2026Version v1

Skill contents

SKILL.md

OKR Planning Skill

Overview

Specialized skill for Objectives and Key Results planning and tracking. Enables product teams to set effective OKRs, track progress, and maintain alignment with organizational goals.

Capabilities

OKR Creation

Generate OKRs from strategic objectives
Validate KR measurability and specificity
Ensure objectives are inspiring and ambitious
Create nested/cascading OKR structures
Define scoring criteria (0.0-1.0)

Alignment

Align team OKRs with company OKRs
Map dependencies between team OKRs
Identify coverage gaps in objectives
Ensure vertical and horizontal alignment
Create OKR cascade visualizations

Tracking and Reporting

Calculate OKR progress and scores
Generate OKR review reports
Identify at-risk objectives
Track confidence levels over time
Create weekly/monthly check-in templates

Target Processes

This skill integrates with the following processes:

quarterly-roadmap.js - OKR-driven roadmap planning
product-vision-strategy.js - Strategic OKR alignment
metrics-dashboard.js - KR metric tracking
stakeholder-alignment.js - OKR communication

Input Schema

json
{
  "type": "object",
  "properties": {
    "mode": {
      "type": "string",
      "enum": ["create", "review", "score", "align"],
      "description": "Operation mode"
    },
    "strategicContext": {
      "type": "object",
      "properties": {
        "companyObjectives": { "type": "array", "items": { "type": "string" } },
        "teamMission": { "type": "string" },
        "timeframe": { "type": "string" }
      }
    },
    "existingOKRs": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "objective": { "type": "string" },
          "keyResults": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "kr": { "type": "string" },
                "target": { "type": "string" },
                "current": { "type": "string" },
                "confidence": { "type": "number" }
              }
            }
          }
        }
      }
    },
    "inputGoals": {
      "type": "array",
      "items": { "type": "string" },
      "description": "High-level goals to convert to OKRs"
    }
  },
  "required": ["mode"]
}

Output Schema

json
{
  "type": "object",
  "properties": {
    "okrs": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "objective": { "type": "string" },
          "rationale": { "type": "string" },
          "keyResults": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "kr": { "type": "string" },
                "metric": { "type": "string" },
                "baseline": { "type": "string" },
                "target": { "type": "string" },
                "stretch": { "type": "string" },
                "measurable": { "type": "boolean" }
              }
            }
          },
          "alignedTo": { "type": "array", "items": { "type": "string" } }
        }
      }
    },
    "alignment": {
      "type": "object",
      "properties": {
        "coverageScore": { "type": "number" },
        "gaps": { "type": "array", "items": { "type": "string" } },
        "dependencies": { "type": "array", "items": { "type": "object" } }
      }
    },
    "scorecard": {
      "type": "object",
      "properties": {
        "overallScore": { "type": "number" },
        "byObjective": { "type": "array", "items": { "type": "object" } },
        "atRisk": { "type": "array", "items": { "type": "string" } },
        "onTrack": { "type": "array", "items": { "type": "string" } }
      }
    },
    "recommendations": {
      "type": "array",
      "items": { "type": "string" }
    }
  }
}

Usage Example

javascript
const okrs = await executeSkill('okr-planning', {
  mode: 'create',
  strategicContext: {
    companyObjectives: [
      'Achieve $10M ARR',
      'Expand to 3 new markets',
      'Reach 90% customer satisfaction'
    ],
    teamMission: 'Deliver product experiences that drive customer adoption',
    timeframe: 'Q2 2026'
  },
  inputGoals: [
    'Improve user onboarding experience',
    'Launch mobile application',
    'Reduce churn in enterprise segment'
  ]
});

Dependencies

OKR frameworks and best practices
Scoring algorithms

Illustrative Want to see what a5c-ai/OKR Planning would put in front of your model? Preview the rendered body and check its trigger phrases — no LLM call, no signup.

Latest benchmark · publisher runVerified

8/29/2026, 21:22 UTC · 22 cases

Lift

+41%

82% vs 41%

Agent turns

0%

1.0 vs 1.0

Tokens

+76%

3,882.68 vs 2,203.45

fail → pass · 9pass → pass · 9fail → fail · 4

Per-case results (22)

Case	Status	Duration (ms)			Turns			Tokens			Tool calls
Case	Status	Without	With	Δ	Without	With	Δ	Without	With	Δ	Without	With	Δ
case-01 Our product organization is planning for Q3 2026. We need to convert three broad team goals—streamlining user onboarding, expanding API infrastructure, and lowering customer support tickets—into structured OKRs that fit our overall company mission of scaling enterprise adoption. Please break these down into inspiring objectives with measurable key results, including baseline and stretch targets, logic/rationale for each, and how they map to our corporate priorities.	fail→fail	27,737	39,940	+44%	1	1	0%	4,950	6,223	+26%	0	0	—
case-02 We just completed our mid-quarter check-in for Q2. Here is our list of existing objectives and key results along with current metric progress and confidence levels: Objective 1 ('Accelerate platform speed') with KRs sitting at 60% completion and confidence 0.8; Objective 2 ('Grow developer community') with KRs at 30% target and confidence 0.4. Please assess our progress and provide an execution scorecard that highlights overall score, breaks down performance by objective, categorizes items into on-track or at-risk, and lists specific actionable advice.	fail→fail	11,936	16,352	+37%	1	1	0%	2,039	4,282	+110%	0	0	—
case-03 We want to ensure our Q4 marketing and product goals align with our high-level corporate direction of hitting $20M ARR and breaking into EMEA. Below are our departmental objectives and existing team targets. Please analyze our horizontal and vertical strategic alignment, giving us a strategic coverage percentage, highlighting unaddressed gaps or cross-team dependencies, and suggesting recommendations for better goal cohesion.	fail→fail	15,142	29,315	+94%	1	1	0%	2,385	6,390	+168%	0	0	—
case-04 We are preparing the sprint backlog for our payment service squad working on Stripe integration. Please take the goal 'Allow users to save secondary credit cards' and break it down into three detailed Agile user stories with acceptance criteria formatted in standard user story structure (As a... I want to... So that...).	pass→pass	13,510	16,234	+20%	1	1	0%	2,573	4,095	+59%	0	0	—
case-05 Our finance team provided Q1 operational figures for our CloudSync SaaS product: $120,000 fully loaded sales and marketing spend, 40 new enterprise logos acquired, average Monthly Recurring Revenue (MRR) per user of $500, and gross margin of 80%. Please compute our Customer Acquisition Cost (CAC) and CAC Payback Period in months.	pass→pass	7,831	9,347	+19%	1	1	0%	1,294	3,064	+137%	0	0	—
case-06 Our core engineering team needs a Product Requirement Document (PRD) for adding multi-factor authentication (MFA) via TOTP authenticator apps in our enterprise admin portal. Please draft a PRD outlining problem statement, functional requirements, non-functional security requirements, and technical constraints.	pass→pass	31,560	28,735	-9%	1	1	0%	6,238	6,411	+3%	0	0	—
case-07 Our DevOps team at DataVault wants to set Q3 OKRs to improve system reliability and speed up deployment pipelines. Strategic context includes company objectives ('Maintain 99.99% uptime', 'Reduce customer churn to under 2%') and team mission ('Deliver resilient infrastructure'). Convert the goal 'Improve deployment pipeline speed' into structured JSON output containing objective, rationale, key results with metrics/baselines/targets, and strategic alignment.	fail→pass	8,404	12,022	+43%	1	1	0%	1,904	3,300	+73%	0	0	—
case-08 For our mobile application team working on FinTech App V2, convert the goal 'Boost app store user ratings' into a formal OKR. Provide the output in JSON format, ensuring each key result contains standard metric tracking fields including an explicit boolean indicating if the metric is quantitative.	fail→pass	12,978	8,652	-33%	1	1	0%	2,224	3,068	+38%	0	0	—
case-09 At Acme Analytics, we are reviewing end-of-quarter performance for Objective 'Enhance Data Pipeline Throughput'. Key Result 1 (increase TPS from 1,000 to 5,000) reached 4,200 TPS (confidence 0.9). Key Result 2 (reduce processing latency from 200ms to 50ms) reached 120ms (confidence 0.5). Evaluate this performance and provide a scorecard JSON. Ensure all numerical scores follow standard OKR 0.0 to 1.0 scoring decimal range.	fail→pass	10,238	19,404	+90%	1	1	0%	2,264	4,521	+100%	0	0	—
case-10 Evaluate our Q1 check-in for the Customer Success team at SaaSify. Objective: 'Increase Enterprise Account Expansion'. KR1: 'Achieve $2M net new expansion ARR' (current: $0.4M, confidence: 0.3). KR2: 'Maintain quarterly retention at 95%' (current: 94%, confidence: 0.85). Generate a JSON scorecard categorizing low-confidence/low-progress goals into the at-risk list.	fail→pass	8,895	14,115	+59%	1	1	0%	1,831	4,205	+130%	0	0	—
case-11 Our executive team set corporate goals for FY26: 1) Double International Revenue, 2) Launch AI Copilot feature, 3) Achieve ISO 27001 Certification. The Product team submitted OKRs focusing solely on the AI Copilot feature and international localization. Analyze strategic alignment and return JSON showing coverage score and identifying unaddressed company goals.	fail→pass	8,872	15,080	+70%	1	1	0%	1,769	3,723	+110%	0	0	—
case-12 The Growth team at E-Com Marketplace set an OKR to 'Launch Instant One-Click Checkout'. However, this depends on the Payments team updating the PCI compliance layer and the Infrastructure team scaling database write throughput. Run strategic alignment analysis and generate JSON documenting cross-team dependencies.	pass→pass	15,355	13,315	-13%	1	1	0%	2,738	3,731	+36%	0	0	—
case-13 We ran an OKR review for our Q2 marketing goals at CloudOps Inc. Objective: 'Dominate Search Engine Visibility'. KRs have 0.2 confidence and zero baseline metrics were defined. Evaluate these OKRs and return JSON output containing specific recommendations for improving OKR quality.	pass→pass	14,308	11,494	-20%	1	1	0%	2,823	3,314	+17%	0	0	—
case-14 Company Objective: 'Scale Enterprise Platform to 500k DAU'. Team: Platform Infrastructure. Input goal: 'Upgrade core database cluster'. Generate a JSON OKR where the objective explicitly maps back to the corporate objective using the alignment properties.	fail→pass	7,192	13,837	+92%	1	1	0%	1,462	3,568	+144%	0	0	—
case-15 Assess progress for Logistics Squad Q3 OKR: 'Reduce order fulfillment time from 48h to 12h'. Current fulfillment time is 36h with confidence rating dropping from 0.8 to 0.3 due to warehouse labor shortages. Return JSON review report highlighting score and risk status.	fail→pass	6,575	11,638	+77%	1	1	0%	1,433	3,276	+129%	0	0	—
case-16 Convert two distinct goals for Logistics App into OKRs: Goal 1: 'Improve driver route optimization efficiency', Goal 2: 'Reduce battery consumption of mobile driver app by 30%'. Output a structured JSON containing an okrs array with two distinct objective objects.	pass→pass	6,564	12,134	+85%	1	1	0%	1,509	3,336	+121%	0	0	—
case-17 Score our Q3 product engineering OKRs for StreamVideo Inc. Objective 1: 'Reduce video buffering latency' (KR target 100ms, actual 95ms, confidence 0.95). Objective 2: 'Launch Android TV app' (KR target 100% feature parity, actual 20%, confidence 0.2). Generate JSON scorecard distinguishing on-track versus at-risk objectives.	pass→pass	7,607	9,631	+27%	1	1	0%	1,632	3,244	+99%	0	0	—
case-18 Assess departmental alignment for HealthTech Corp Q4 goals. Corporate Objective: 'Achieve HIPAA Compliance across all services'. Department Goals: Security squad setting HIPAA audit OKR, Frontend squad setting UI redesign OKR. Provide strategic alignment JSON detailing coverageScore, gaps, and recommendations.	pass→pass	12,737	11,818	-7%	1	1	0%	2,226	3,122	+40%	0	0	—
case-19 A product manager in our Customer Support squad submitted a qualitative key result: 'Make customer support feel much friendlier and happier'. Refactor this into a proper quantitative key result for the objective 'Improve customer support experience' and return structured JSON.	fail→pass	10,786	12,238	+13%	1	1	0%	1,806	3,223	+78%	0	0	—
case-20 Calculate overall score for Q1 OKRs at PayTech Ltd. Objective 1 score: 0.80. Objective 2 score: 0.40. Return a scorecard JSON object with overallScore and breakdown by objective.	fail→pass	3,719	7,296	+96%	1	1	0%	637	2,430	+281%	0	0	—
case-21 Formulate an OKR for CyberSec Solutions to 'Automate vulnerability scanning in CI/CD pipeline'. Return a JSON object with okrs array, ensuring each objective contains explicit rationale explaining strategic importance.	pass→pass	7,785	9,549	+23%	1	1	0%	1,122	3,070	+174%	0	0	—
case-22 Assess alignment for SalesOps team. Company objective: 'Expand Enterprise Sales in APAC'. Team OKR: 'Hire 5 APAC enterprise account executives and close 10 APAC deals'. Perform alignment check and return JSON.	fail→fail	9,222	13,010	+41%	1	1	0%	1,617	3,823	+136%	0	0	—

These cases were also screened by the skill’s intent / safety pass.See the Trust review ↗Reproduce this benchmark in Colab ↗

How this skill was measured

DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +41 percentage points is the difference between those two pass rates over the 22 comparable cases.

Model measured: gemini-3.6-flash
Graded by: gemini-3.6-flash
Grading method: judged
Verification: verified
Pass rate without the skill: 40.9%
Pass rate with the skill: 81.8%
Cases attempted: 22
Cases counted toward lift: 22
Cases that regressed: 0
Skill version measured: v1
Run completed: 8/29/2026, 21:22 UTC

Measured example — same prompt, with vs. without the skill · from the benchmark run · case case-07

Prompt

Our DevOps team at DataVault wants to set Q3 OKRs to improve system reliability and speed up deployment pipelines. Strategic context includes company objectives ('Maintain 99.99% uptime', 'Reduce customer churn to under 2%') and team mission ('Deliver resilient infrastructure'). Convert the goal 'Improve deployment pipeline speed' into structured JSON output containing objective, rationale, key results with metrics/baselines/targets, and strategic alignment.

Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.

Show both answers

SkillScore blends 4 signals1 of 4 complete

BenchmarkPass rate WITH skill on a verified run82

Live evalNeeds ≥10 evaluated traces in 30 days

AI ratingNeeds ≥10 rated traces

AdoptionNeeds ≥10 serves across ≥2 orgs in 30 days

Efficiency · separate axis (at equal correctness)+0% turns+51% tokens

Shown for transparency; not credited unless a verified run shows no correctness regression.

Backed by 1 of 4 signals — each added signal makes the score more robust.

Verified on gemini-3.6-flash · re-tested 25 days ago

Other measured skills in the registry, with their headline benchmark lift.