OKR Progress Tracker#

Track, evaluate, and forecast OKR (Objectives and Key Results) progress by analyzing your OKR definitions, current metrics, and time elapsed in the quarter. Identifies at-risk objectives, flags stalled key results, and provides data-driven recommendations for course correction.

Usage#

Invoke this skill when you need to assess OKR progress, prepare for a quarterly review, or identify which objectives need attention.

Basic invocation:

Track OKR progress from okrs.yaml Evaluate our Q2 OKRs in /path/to/okrs.md

With options:

Score OKRs and predict end-of-quarter outcomes Which OKRs are at risk? Check /team/okrs/ Generate an OKR health report for the leadership review

The agent reads your OKR files, calculates progress, and produces a structured assessment.

How It Works#

Step 1: Parse OKR Definitions#

The agent reads OKR files in any of the supported formats and builds an internal model.

Supported formats:

Markdown format:

markdown

## Objective: Improve platform reliability
- KR1: Reduce P1 incidents from 12/quarter to 3/quarter (current: 7)
- KR2: Achieve 99.95% uptime (current: 99.91%)
- KR3: Mean time to recovery under 15 minutes (current: 23 min)

## Objective: Accelerate developer velocity
- KR1: CI pipeline p95 under 8 minutes (current: 11 min)
- KR2: Deploy frequency from 2/week to 5/week (current: 3/week)
- KR3: Onboarding time for new devs under 3 days (current: 5 days)

YAML format:

yaml

quarter: Q2 2026
start_date: 2026-04-01
end_date: 2026-06-30
objectives:
  - name: Improve platform reliability
    owner: platform-team
    key_results:
      - description: Reduce P1 incidents per quarter
        start_value: 12
        target_value: 3
        current_value: 7
        unit: incidents/quarter
        direction: decrease
      - description: Achieve monthly uptime target
        start_value: 99.85
        target_value: 99.95
        current_value: 99.91
        unit: percent
        direction: increase

JSON format:

json

{
  "quarter": "Q2 2026",
  "objectives": [
    {
      "name": "Improve platform reliability",
      "key_results": [
        {
          "description": "Reduce P1 incidents",
          "start": 12, "target": 3, "current": 7
        }
      ]
    }
  ]
}

The agent auto-detects the format and normalizes internally. It handles partial data gracefully, asking the user for missing fields only when critical (like target values).

Step 2: Determine Quarter Timeline#

The agent calculates where you are in the quarter:

text

Quarter: Q2 2026 (April 1 - June 30)
Today: April 30, 2026
Elapsed: 30 of 91 days (33.0%)
Remaining: 61 days
Weeks remaining: 8.7

This timeline is critical for pace analysis: if 33% of time has passed, key results should ideally be at ~33% progress to be on track.

Step 3: Score Each Key Result#

For each key result, the agent calculates:

Progress percentage:

text

progress = (current - start) / (target - start) * 100

Example: P1 incidents
  start=12, target=3, current=7
  progress = (12 - 7) / (12 - 3) * 100 = 55.6%

Pace ratio (progress vs. time elapsed):

text

pace = progress_pct / time_elapsed_pct

Example: 55.6% progress / 33.0% time elapsed = 1.68x pace
  > 1.0 = ahead of schedule
  = 1.0 = on track
  < 1.0 = behind schedule
  < 0.5 = significantly at risk

Projected end-of-quarter value (linear extrapolation):

text

projected = start + (current - start) * (total_days / elapsed_days)

Example: P1 incidents
  projected = 12 + (7 - 12) * (91 / 30) = 12 + (-5 * 3.03) = -3.2
  Clamped to achievable range: projected = 0 incidents (exceeds target)

Confidence level based on:

• Pace ratio
• Variance in progress (if historical data points available)
• Time remaining (more time = more uncertainty)
• Whether progress follows a linear, exponential, or step-function pattern

Step 4: Classify Key Result Health#

Each key result receives a health classification:

StatusCriteriaSymbolOn TrackPace ratio >= 0.9[=]Needs AttentionPace ratio 0.6 - 0.9[~]At RiskPace ratio 0.3 - 0.6[!]Off TrackPace ratio < 0.3[X]AchievedCurrent meets or exceeds target[+]Not StartedNo progress from start value[-]

The agent adjusts thresholds based on quarter progress. Early in the quarter, it applies wider tolerances (some KRs ramp up late). Late in the quarter, thresholds tighten.

Step 5: Roll Up to Objective Health#

Each objective score is the weighted average of its key results:

text

Objective Score = average(KR1_progress, KR2_progress, KR3_progress)

The agent applies a "weakest link" modifier: if any single KR is Off Track, the objective health is capped at "Needs Attention" regardless of other KRs, since objectives require all key results to be meaningful.

Objective health classifications:

• Strong (0.7-1.0): Most KRs on track or achieved
• Moderate (0.4-0.7): Mixed progress, some KRs lagging
• Weak (0.0-0.4): Majority of KRs behind schedule
• Critical: Any KR at 0% progress past 50% of quarter

Step 6: Trend Analysis (If Historical Data Available)#

If the user provides multiple snapshots or the OKR file includes a history of values, the agent performs trend analysis:

• Velocity calculation: rate of progress per week
• Acceleration/deceleration: is progress speeding up or slowing down?
• Plateau detection: has a KR stalled (no movement in 2+ weeks)?
• Trajectory plotting: when will the KR hit its target at current velocity?

text

KR: Reduce P1 incidents (target: 3)
  Week 1: 12 -> 11 (-1)
  Week 2: 11 -> 9  (-2)
  Week 3: 9  -> 7  (-2)
  Week 4: 7  -> 7  (0)   <-- STALL DETECTED

  Current velocity: -1.25/week (slowing)
  At current velocity: target reached in week 7 (on schedule, but decelerating)
  Risk: Plateau pattern suggests operational changes needed

Step 7: Generate Recommendations#

For each at-risk or off-track key result, the agent produces actionable recommendations:

For stalled KRs:

• Identify what changed around the stall point
• Suggest owner check-in or scope reassessment
• Recommend breaking the KR into intermediate milestones

For behind-pace KRs:

• Calculate the required weekly progress to still hit the target
• Flag if the required pace is unrealistic (e.g., need 3x current velocity)
• Suggest scope reduction, additional resources, or target adjustment

For on-track KRs:

• Identify if the KR was sandbagged (too easy) based on early completion
• Suggest stretch goals if applicable

For objectives with mixed KRs:

• Identify which KR is the bottleneck
• Suggest rebalancing effort across KRs
• Flag dependency chains between KRs

Step 8: Produce the Report#

The agent generates a structured report:

text

# OKR Progress Report — Q2 2026
# Snapshot: April 30, 2026 (33% through quarter)

## Overall Health: Moderate (0.58)
  2 objectives on track, 1 needs attention

## Objective 1: Improve Platform Reliability
   Health: Strong (0.72) | Owner: platform-team

   [=] KR1: Reduce P1 incidents to 3/quarter
       Progress: 55.6% | Pace: 1.68x | Projected: 0 (exceeds target)
       Status: Ahead of schedule

   [~] KR2: Achieve 99.95% uptime
       Progress: 60.0% | Pace: 1.18x | Projected: 99.97%
       Status: On track, slight deceleration in week 4

   [!] KR3: MTTR under 15 minutes
       Progress: 27.6% | Pace: 0.84x | Projected: 18.2 min
       Status: NEEDS ATTENTION — will miss target at current pace
       Recommendation: Need to improve by 1.3 min/week (currently 0.8 min/week).
         Consider automated runbook rollout to reduce manual investigation time.

## Objective 2: Accelerate Developer Velocity
   Health: Moderate (0.51) | Owner: dx-team
   ...

## At-Risk Summary
  1. KR3 (MTTR) — pace 0.84x, needs 63% increase in improvement rate
  2. KR5 (Onboarding) — pace 0.55x, recommend reducing target to 4 days

## Recommendations
  1. Schedule deep-dive on MTTR with on-call team this week
  2. Reassess onboarding KR target — 3 days may be unrealistic given hiring freeze
  3. KR1 (P1 incidents) likely to be achieved early — consider stretch target

Output#

The agent produces:

• Executive summary: overall OKR health score, count of on-track vs. at-risk objectives
• Per-objective breakdown: health score, owner, and per-KR detail
• Per-KR metrics: progress %, pace ratio, projected end value, health status
• At-risk register: ranked list of KRs most likely to miss targets
• Recommendations: 3-7 specific, actionable recommendations with rationale
• Timeline context: days remaining, percentage through quarter, required pace adjustments

Output formats:

• Narrative (default): human-readable report for standup or review meetings
• Table: compact tabular view for dashboards
• Detailed: includes trend analysis, historical data points, and confidence intervals

Advanced Features#

Cascade Analysis#

When OKRs reference each other (company -> team -> individual), the agent traces the cascade:

text

Company OKR: Grow revenue 30% YoY
  └─ Team OKR: Launch 3 enterprise features
      └─ Individual OKR: Ship SSO integration by May 15
         Status: At Risk (blocked on IdP vendor)
         Impact: Delays team OKR, which delays company revenue feature pipeline

Cross-Team Dependency Detection#

The agent identifies when one team's KR depends on another team's work:

text

WARNING: Team Alpha's KR2 (API v3 migration) depends on
Team Beta's KR1 (schema redesign), which is Off Track.
Team Alpha's KR2 is at risk regardless of their own progress.

Scoring Calibration#

The agent supports different scoring methodologies:

• Google-style (0.0-1.0): 0.7 = fully met expectations, 1.0 = exceptional
• Binary: met/not met per KR
• Percentage: raw progress percentage
• Traffic light: green/yellow/red

Quarter-over-Quarter Comparison#

If previous quarter OKR files are available, the agent compares:

• Score improvement or regression per objective area
• KR target ambition levels (are targets getting harder or easier?)
• Recurring at-risk themes (same area struggling quarter after quarter)

Tips for Best Results#

• Include start_value, target_value, and current_value for each KR to get accurate scoring
• Specify direction (increase/decrease) when it is not obvious from context
• Update current_value weekly for trend analysis to work
• Include owner information to enable team-level rollups
• Store OKR files in version control to enable quarter-over-quarter comparison
• Use consistent KR formats: quantitative targets are scored much more accurately than qualitative ones