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grainulationgrainulation/grainulator/skills/analytics/SKILL.md

analytics

Skill86 starsChanged 9 days agoMITView on GitHub

Sprint analytics — type distributions, stale claims, velocity, prediction scoring

69 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use popups, free-tools and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • CesarjoquinSkill

    popups

    When the user wants to create or optimize popups, modals, overlays, slide-ins, or banners for conversion purposes. Also use when the user mentions "exit intent," "popup conversions," "modal optimization," "lead capture popup," "email popup," "announcement banner," "overlay," "collect emails with a popup," "exit popup," "scroll trigger," "sticky bar," or "notification bar." Use this for any overlay or interrupt-style conversion element. For forms outside of popups, see cro. For general page conversion optimization, see cro.

    Also in 23 projects that use this

  • CesarjoquinSkill

    free-tools

    When the user wants to plan, evaluate, or build a free tool for marketing purposes — lead generation, SEO value, or brand awareness. Also use when the user mentions "engineering as marketing," "free tool," "marketing tool," "calculator," "generator," "interactive tool," "lead gen tool," "build a tool for leads," "free resource," "ROI calculator," "grader tool," "audit tool," "should I build a free tool," or "tools for lead gen." Use this whenever someone wants to build something useful and give it away to attract leads or earn links. For downloadable content lead magnets (ebooks, checklists, templates), see lead-magnets.

    Also in 24 projects that use this

  • coreyhaines31Skill

    marketing-council

    When the user wants multiple expert perspectives on a marketing question — a simulated board of advisors staffed by legendary marketers (Seth Godin, David Ogilvy, Eugene Schwartz, April Dunford, Rory Sutherland, Alex Hormozi, Byron Sharp, and more). Also use when the user mentions 'marketing council,' 'board of advisors,' 'advisory board,' 'what would Seth Godin say,' 'what would Ogilvy think,' 'channel Hormozi,' 'get multiple perspectives,' 'debate this,' 'have the council review,' 'marketing mentors,' or asks how a famous marketer would approach their problem. The council gives each advisor's take through their documented frameworks, surfaces where they disagree, and synthesizes a recommendation. For executing the winning direction, hand off to positioning, offers, copywriting, ads, or the relevant skill.

    Also in 19 projects that use this

  • roerohanSkill

    emails

    When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," "lifecycle emails," "trigger-based emails," "email funnel," "email workflow," "what emails should I send," "welcome series," or "email cadence." Use this for any multi-email automated flow. For cold outreach emails, see cold-email. For in-app onboarding, see onboarding.

    Also in 21 projects that use this

  • ukunal91appSkill

    community-marketing

    Build and leverage online communities to drive product growth and brand loyalty. Use when the user wants to create a community strategy, grow a Discord or Slack community, manage a forum or subreddit, build brand advocates, increase word-of-mouth, drive community-led growth, engage users post-signup, or turn customers into evangelists. Trigger phrases: "build a community," "community strategy," "Discord community," "Slack community," "community-led growth," "brand advocates," "user community," "forum strategy," "community engagement," "grow our community," "ambassador program," "community flywheel.

    Also in 26 projects that use this

  • coreyhaines31Skill

    marketing-loops

    When the user wants to set up a recurring, self-running marketing workflow — a repeatable loop an AI agent runs on a cadence (weekly, daily, on a trigger) rather than a one-off task. Also use when the user mentions 'marketing loop,' 'recurring marketing workflow,' 'automate my marketing,' 'marketing on autopilot,' 'weekly marketing review,' 'ad fatigue check,' 'weekly ads check,' 'content refresh loop,' 'churn watch,' 'ranking drop alert,' 'run my SEO,' 'SEO operator,' 'daily SEO agent,' 'run my outbound,' 'AI SDR,' 'reply triage,' 'always-on marketing,' 'marketing automation workflow,' or 'run this every week.' Use this to pick, adapt, and schedule an ongoing marketing loop that orchestrates the other marketing skills. For one-off marketing ideas, see marketing-ideas. For the experimentation loop specifically, see ab-testing.

    Also in 10 projects that use this

  • +6 more from Cesarjoquin

The file

We split this skill into the rules it gives an agent

6 rules. 0 are common, 1 is distinctive, and 5 are very specific to this project.

  • 0

    Common

    Most of the 58 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 5

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    If no active sprint is found, check the current working directory for a claims.json file.

    line 26
  2. Very specific:

    If still not found, stop and tell the user: "No active sprint detected.

    line 27
  3. Very specific:

    Run grainulator analytics velocity <dir> --json, then display the analytics summary:

    line 40
  4. Very specific:

    If the user passed --full, run the report command directly and write the output to <dir>/output/analytics.html (use an absolute resolved …

    line 71
  5. Distinctive:

    If the sprint appears to be in a late phase (has recommendations, has a brief, or the user mentioned shipping), suggest:

    line 74
  6. Very specific:

    If the user passed --calibrate, run grainulator analytics calibrate <dir> and display the prediction accuracy results.

    line 80

“Common” is measured: kept by at least 6 in 10 of the 58 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

/analytics -- Sprint analytics and retrospective

The user wants quantitative analysis of the current sprint: claim type distributions, evidence quality, stale claims, and velocity metrics.

Arguments

$ARGUMENTS

Optional: --full to generate an HTML retrospective report. --calibrate to run prediction scoring.

Instructions

  1. Detect the sprint directory:
    • Honor the explicit user directory, active sprint in AGENTS.md, or configured task context before checking cwd. Pass the resolved dir to grainulator.status.
    • Identify the sprint directory from the status output (the directory containing claims.json).
    • If no active sprint is found, check the current working directory for a claims.json file.
    • If still not found, stop and tell the user: "No active sprint detected. Run /init to start one."
    • Store the resolved directory as <dir> for subsequent steps.
  2. Run type/evidence analysis:
    • Execute: grainulator analytics analyze <dir>
    • This returns claim type distribution (constraint, factual, estimate, risk, recommendation, feedback) and evidence tier distribution (stated, web, documented, tested, production).
    • Capture the output for the summary.
  3. Run stale claim detection:
    • Execute: grainulator analytics decay <dir> --days 7
    • This checks age since creation/update or a linked full-support witness. Partial support and contradictions do not renew freshness. It reports volatile-evidence stale claims and older decaying claims separately.
    • Capture the list of stale claim IDs and their ages.
  4. Run grainulator analytics velocity <dir> --json, then display the analytics summary:

    Analytics: <sprint-slug>
    ─────────────────────────────
    
    Claim distribution:
      constraint: <n>  |  factual: <n>  |  estimate: <n>
      risk: <n>  |  recommendation: <n>  |  feedback: <n>
    
    Evidence quality:
      stated: <n>  |  web: <n>  |  documented: <n>  |  tested: <n>  |  production: <n>
    
    Weak areas:
      - <material gaps relative to the task, not missing tiers or a quota>
      - <a stated stakeholder constraint can be appropriate evidence of that requirement>
    
    Stale claims (<n> total):
      - <id>: "<summary>" — <age> days stale
      - ...
    
    Velocity:
      <actual output from velocity>
  5. Suggest full retrospective:
    • Tell the user they can generate a full HTML retrospective report:
      For a full retrospective report:
        grainulator analytics report <dir> -o <dir>/output/analytics.html
    • If the user passed --full, run the report command directly and write the output to <dir>/output/analytics.html (use an absolute resolved directory).
  6. Recommend calibration if sprint is complete:
    • If the sprint appears to be in a late phase (has recommendations, has a brief, or the user mentioned shipping), suggest:
      Sprint looks complete. Score your predictions:
        /calibrate --outcome "what actually happened"
        grainulator analytics calibrate <dir>
    • If the user passed --calibrate, run grainulator analytics calibrate <dir> and display the prediction accuracy results.
  7. Suggest next steps based on the findings:

    Auto
    
    - <authorized next action>
    
    Manual
    
    - <action requiring the user, or None.>

    Tailor the suggestions:

    • Stale claims exist -> suggest /challenge or /research on the stalest
    • Weak evidence base -> suggest /witness or /research
    • Type concentration -> assess whether the task actually requires another perspective; do not add filler claims
    • Sprint looks healthy -> suggest /brief or /present

Host access

Use available grainulator MCP tools, passing the active sprint dir explicitly for evidence operations. If a tool is unavailable, use the local grainulator CLI (or node <checkout>/bin/grainulator.js). Read sibling skill files directly when slash commands are unavailable. Resolve template paths relative to this skill’s checkout when CLAUDE_PLUGIN_ROOT is unset. Optional external connectors are not required for local work; use local code, supplied documents, or available web tools. Do not write managed ledger files directly to bypass a missing MCP connection.

Next-step output

For standalone fetch, setup, or read-only orchestration without an evidence sprint, derive next steps from that task. Do not initialize or compile an unrelated ledger just to produce this footer.

When working in an evidence sprint, use the current compiler's next_actions to present exactly two bullet lists labeled Auto and Manual. Auto is work the agent can continue under existing authorization. Manual is only work requiring the user's decision, access, or action. Classify using the current request and constraints; compiler suggestions never grant permission. Continue authorized Auto work without asking again.

Keep 2–3 useful actions total when available, use short concrete labels and commands where useful, and show None. for an empty group. Do not invent work to fill a quota. Never omit next steps merely because compilation is ready or the answer should be brief. Refresh stale compilation first and exclude work the user removed from scope. When the user asks only for next steps, output only these two lists: no findings recap, counts, reasons, or offer to continue.

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