Agent skill

Prd V03 Outcome Definition

by mattgierhart in mattgierhart/PRD-driven-context-engineering

Define measurable success metrics (KPIs) tied to product type during PRD v0.3 Commercial Model.

MITAuto-check passedProduct & Project Management

Install Prd V03 Outcome Definition

skills CLI
$ npx skills add mattgierhart/PRD-driven-context-engineering --skill prd-v03-outcome-definition -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mattgierhart/PRD-driven-context-engineering prd-v03-outcome-definition --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mattgierhart/PRD-driven-context-engineering.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/prd-v03-outcome-definition .claude/skills/prd-v03-outcome-definition && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
prd-v03-outcome-definition
GitHub stars
180
Token cost
~1.9k tokens
SKILL.md length
641 words
Files
4 (incl. references, assets)
Skills in repo
45
Repo updated
First seen
Licence
MIT

At a glance

Define measurable success metrics (KPIs) tied to product type during PRD v0.3 Commercial Model.

  • Works in 6 steps: Vanity metrics as primary: "50K users"… → Traffic without quality: High volume +… → Arbitrary targets: "10% improvement"… → …
  • Requests to define success metrics
  • SKILL.md covers Consumes, Produces, Metric Quality Hierarchy and Product Type × Metric Selection, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Prd V03 Outcome Definition is an agent skill from mattgierhart/PRD-driven-context-engineering. Define measurable success metrics (KPIs) tied to product type during PRD v0.3 Commercial Model. Triggers on requests to define success metrics, set KPI targets, determine what to measure, establish go/no-go thresholds, or when user asks "how do we measure success?", "what metrics matter?", "what's our target?", "how do we know if this works?", "define KPIs", "success criteria". Consumes Product Type Classification (BR-) from v0.2. Outputs KPI- entries with thresholds, evidence sources, and downstream gate linkages.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files and assets (for example `assets/kpi.md`, `references/benchmarks.md` and `references/examples.md`).

It sits in Product & Project Management, covering OKRs and executive reporting, PRD writing and Product metrics. The repository describes itself as: PRD-Led Context Engineering — Memory as Infrastructure. An ontology layer for product teams building products that solve real problems — with AI agents that remember. Gated PRD… The licence is MIT.

When your agent uses it

  • Requests to define success metrics
  • Set KPI targets
  • Determine what to measure
  • Establish go/no-go thresholds

Example prompts

  • “how do we measure success?”
  • “what metrics matter?”
  • “s our target?”
  • “/prd-v03-outcome-definition”

Requirements

  • Pre-approved tools (allowed-tools): Read, Write, Edit, Glob, Grep, WebSearch, WebFetch

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Vanity metrics as primary: "50K users" means nothing if only 500 pay
  2. Traffic without quality: High volume + low engagement = quality problem
  3. Arbitrary targets: "10% improvement" without baseline or benchmark
  4. All lagging, no leading: Can't course-correct if you only see outcomes monthly
  5. Ignoring product type: Clone metrics ≠ Innovation metrics
  6. Unmeasurable outcomes: "Better experience" — how do you know?

What it can do on your machine

Read from SKILL.md and the folder at commit 30ed1b0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Glob
    • Grep
    • WebSearch
    • WebFetch

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Prd V03 Outcome Definition loads about 1.9k tokens when it runs, and up to ~4.2k if it reads all its reference files. Until then it costs about 137 tokens; SKILL.md has 641 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~137
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from mattgierhart/PRD-driven-context-engineering at commit 30ed1b0, republished under its MIT licence (© mattgierhart). 641 words, ~1,907 tokens.

Download SKILL.mdSave it as .claude/skills/prd-v03-outcome-definition/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
prd-v03-outcome-definition
description
Define measurable success metrics (KPIs) tied to product type during PRD v0.3 Commercial Model. Triggers on requests to define success metrics, set KPI targets, determine what to measure, establish go/no-go thresholds, or when user asks "how do we measure success?", "what metrics matter?", "what's our target?", "how do we know if this works?", "define KPIs", "success criteria". Consumes Product Type Classification (BR-) from v0.2. Outputs KPI- entries with thresholds, evidence sources, and downstream gate linkages.
allowed-tools
Read, Write, Edit, Glob, Grep, WebSearch, WebFetch
context
fork

Outcome Definition

Position in HORIZON workflow: v0.2 Product Type Classification → v0.3 Outcome Definition → v0.3 Pricing Model Selection

Consumes

This skill requires prior work from v0.2:

  • BR-* product type entry (from Product Type Classification) — Classification determines which metrics are relevant
  • CFD-* entries (from Problem Framing and Competitive Landscape) — Customer evidence about desired outcomes
  • Market benchmarks and competitor metrics — Reference data for Tier 1/2 targets

This skill assumes v0.2 classification is complete.

Produces

This skill creates/updates:

  • KPI-* entries (outcome definitions) — Measurable success metrics tied to product type
  • BR-* outcome rules (optional) — Constraints derived from KPI thresholds (e.g., "Launch blocked if LTV:CAC < 3:1")
  • Success criteria artifact — Dashboard of leading + lagging indicators that define product-market fit

All KPI entries should include:

  • confidence: 2-3/5 (based on benchmark evidence, not just assumptions)
  • Evidence source (competitor benchmarks, CFD validation, industry reports)
  • Forward target: "Would move to 4/5 if we observe real customer data"

Example KPI entry with confidence:

markdown
KPI-001: Time to First Revenue

Type: Tier 1 (Revenue)
Category: Lagging
Definition: Days from market signal identification to first paying customer
Target: ≤14 days
Confidence: 2/5 (source: GearHeart-methodology + 0-customer-validation)
Evidence: BR-001 (GearHeart standard); No pre-customer validation yet
Next Target: "Would move to 4/5 if actual customer reaches paying status in ≤14 days"
Downstream Gate: v0.5 Red Team — if not hit by Day 21, evaluate pivot

---

KPI-002: Conversion Rate (Trial → Paid)

Type: Tier 2 (Leading Indicator)
Category: Leading
Definition: (Paid customers / Trial signups) × 100, measured over 60-day trial period
Target: ≥15% (benchmark: SaaS median 10-15%)
Confidence: 3/5 (source: SaaS-benchmarks + 1-SMB-validation-conversation)
Evidence: CFD-042 (competitive landscape shows SMB conversion patterns)
Next Target: "Would move to 4/5 if we see actual cohort conversion in our product"
Downstream Gate: v0.7 Build Execution — EPIC complete when KPI-002 validated

Metric Quality Hierarchy

Not all metrics are equal. Use this tier system:

TierMetric TypesWhy It Matters
Tier 1Revenue (MRR, first dollar, ACV), Churn (logo, NRR), LTV:CACRevenue validates market fit. "First dollar IS the proof."
Tier 2Conversion rates (trial→paid, lead→customer), Time to Value, ActivationLeading indicators that predict Tier 1 outcomes
Tier 3Engagement (DAU, sessions), Feature adoption, NPS"Nice to know" — only track if tied to Tier 1/2

Rule: Every product needs at least one Tier 1 metric. Tier 3 metrics without Tier 1/2 correlation are vanity metrics.

Product Type × Metric Selection

Metrics must align with product type from v0.2 classification:

Product TypePrimary MetricsAnti-Metrics (Avoid)
CloneFeature parity score, Price delta vs. leader, TTFV vs. leaderGeneric engagement (doesn't prove you beat leader)
UndercutPrice per [unit] vs. leader, Niche conversion rate, CAC in target segmentBroad market share (you're niche by design)
UnbundleCategory NPS vs. platform, Vertical retention, Feature depth usagePlatform-level metrics (irrelevant to your slice)
SliceMarketplace ranking, Install→activate rate, Platform retention liftTAM metrics (platform owns the market)
WrapperTime saved per workflow, API reliability, Integration adoptionStandalone usage (value is in connection)
InnovationEducation→activation conversion, Behavioral change rate, Reference customersUser counts without activation (people try, don't convert)
Show full SKILL.md (279 more words)Show less

Leading vs. Lagging Framework

Every product needs BOTH:

Leading Indicators (actionable now, predict outcomes):

  • Sequences sent, open rates, trial starts
  • Time to first value, activation rate
  • Feature adoption in first 7 days

Lagging Indicators (confirm strategy worked):

  • MRR, churn rate, LTV:CAC
  • Net Revenue Retention (NRR)
  • Customer count, logo churn

Pattern: Track leading weekly, lagging monthly. If leading indicators fail, you can pivot before lagging indicators confirm disaster.

Target-Setting Rules

Targets must be evidence-based, never arbitrary:

Good targets (use these approaches):

  • Competitor benchmark × safety margin: "SMB churn benchmark 3-5% → use 5%"
  • Revenue gates: "First dollar by Day 14" (Signal → $1: 14 days)
  • Ratio thresholds: "LTV:CAC ≥ 3:1"
  • Time bounds: "TTFV < 5 minutes for self-serve"

Bad targets (anti-patterns):

  • Round numbers without evidence: "10% improvement"
  • Engagement without revenue tie: "1000 DAU"
  • Aspirational without baseline: "Best in class retention"

Output Template

Create KPI- entries in this format:

KPI-XXX: [Metric Name]
Type: [Tier 1 | Tier 2 | Tier 3]
Category: [Leading | Lagging]
Definition: [Exact calculation formula]
Target: [Specific threshold with evidence source]
Evidence: [CFD-XXX or benchmark source]
Downstream Gate: [Which decision uses this — e.g., "v0.5 Red Team kill criteria"]
Measurement: [How/when measured — e.g., "Weekly via Mixpanel"]

Example KPI- entry:

KPI-001: Time to First Revenue
Type: Tier 1
Category: Lagging
Definition: Days from market signal identification to first paying customer
Target: ≤14 days (GearHeart standard: Signal → $1: 14 days)
Evidence: BR-001 (GearHeart methodology)
Downstream Gate: v0.5 Red Team — if not hit by Day 21, evaluate pivot
Measurement: Manual tracking in PRD changelog

Anti-Patterns to Avoid

  1. Vanity metrics as primary: "50K users" means nothing if only 500 pay
  2. Traffic without quality: High volume + low engagement = quality problem
  3. Arbitrary targets: "10% improvement" without baseline or benchmark
  4. All lagging, no leading: Can't course-correct if you only see outcomes monthly
  5. Ignoring product type: Clone metrics ≠ Innovation metrics
  6. Unmeasurable outcomes: "Better experience" — how do you know?

Downstream Connections

KPI- entries feed into:

ConsumerWhat It UsesExample
v0.5 Red TeamKill thresholds"If KPI-001 not hit by Day 21, pivot"
v0.7 Build ExecutionEPIC acceptance criteria"EPIC complete when KPI-002 validated"
v0.9 GTMLaunch dashboardTrack KPI-001, KPI-003 post-launch
BR- Business RulesDerived constraints"BR-XXX: No launch if LTV:CAC <3:1"

Detailed References

  • Good/bad examples: See references/examples.md
  • Benchmark sources: See references/benchmarks.md
  • KPI template worksheet: See assets/kpi.md

© mattgierhart, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references, assets) in .claude/skills/prd-v03-outcome-definition of mattgierhart/PRD-driven-context-engineering.

  • SKILL.md
  • assets/kpi.md
  • references/benchmarks.md
  • references/examples.md

Open the folder on GitHubat commit 30ed1b0

Compare with similar skills

Prd V03 Outcome Definition next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Prd V03 Outcome Definition compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
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Schematicblader/schematic241—~2.2kAutomated safety check: PassMIT
Prdjuanandresgs/claude-ctrl193—~2.9kAutomated safety check: PassNone
Discovery Synthesisandreaskelm/pm-brain234—~2.3kAutomated safety check: PassCustom licence
App Spec Packagerinstructa/agent-skills139—~1.5kAutomated safety check: PassNone

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Questions about Prd V03 Outcome Definition

What does Prd V03 Outcome Definition do?

Define measurable success metrics (KPIs) tied to product type during PRD v0.3 Commercial Model. Prd V03 Outcome Definition is an agent skill from mattgierhart/PRD-driven-context-engineering.3 Commercial Model.

When should I use Prd V03 Outcome Definition?

Prd V03 Outcome Definition fits situations like: requests to define success metrics; set KPI targets; determine what to measure; establish go/no-go thresholds.

How do I install Prd V03 Outcome Definition in Claude Code?

Run `npx skills add mattgierhart/PRD-driven-context-engineering --skill prd-v03-outcome-definition -a claude-code`. Or copy the skill folder (.claude/skills/prd-v03-outcome-definition in mattgierhart/PRD-driven-context-engineering) into .claude/skills/prd-v03-outcome-definition in your project. Claude Code loads it when a task matches its description.

How do I install Prd V03 Outcome Definition in Codex?

Run `npx skills add mattgierhart/PRD-driven-context-engineering --skill prd-v03-outcome-definition -a codex`. Or copy the skill folder (.claude/skills/prd-v03-outcome-definition in mattgierhart/PRD-driven-context-engineering) into .agents/skills/prd-v03-outcome-definition in your project. Codex loads it when a task matches its description.

Can I use Prd V03 Outcome Definition in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mattgierhart/PRD-driven-context-engineering --skill prd-v03-outcome-definition -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/prd-v03-outcome-definition, .gemini/skills/prd-v03-outcome-definition, .github/skills/prd-v03-outcome-definition and .opencode/skills/prd-v03-outcome-definition in your project.

What does Prd V03 Outcome Definition need to run?

SKILL.md names no scripts, command-line tools or credentials: Prd V03 Outcome Definition is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit, Glob, Grep, WebSearch, WebFetch.

Does Prd V03 Outcome Definition access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Prd V03 Outcome Definition safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Prd V03 Outcome Definition use?

Prd V03 Outcome Definition is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Prd V03 Outcome Definition use?

About 1.9k tokens (SKILL.md is roughly 7.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.3k tokens, read only when the agent opens those files.

What are the alternatives to Prd V03 Outcome Definition?

Skills that share tags, products or a category with Prd V03 Outcome Definition: Pm Spec (sanqiufong/slides-from-anything, 132 stars), Schematic (blader/schematic, 241 stars), Prd (juanandresgs/claude-ctrl, 193 stars) and Discovery Synthesis (andreaskelm/pm-brain, 234 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Prd V03 Outcome Definition?

mattgierhart (a GitHub user) maintains it in mattgierhart/PRD-driven-context-engineering, which has 180 GitHub stars. The repository holds 45 skills in this directory. The repository was last updated on August 31, 2026.

Source: mattgierhart/PRD-driven-context-engineering on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.