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Agent skill

Productspec

by gokulrajaram in gokulrajaram/ProductSpec

A skill your agent uses when implementing, reviewing, planning, or changing work governed by a Product Spec.

MITAuto-check passedProduct & Project Management

Install Productspec

skills CLI
$ npx skills add gokulrajaram/ProductSpec --skill productspec -a claude-code

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

GitHub CLI
$ gh skill install gokulrajaram/ProductSpec productspec --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/gokulrajaram/ProductSpec.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/productspec .claude/skills/productspec && 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
productspec
GitHub stars
306
Token cost
~1.3k tokens
SKILL.md length
727 words
Files
1
Skills in repo
2
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when implementing, reviewing, planning, or changing work governed by a Product Spec.

  • Works in 7 steps: Problem: who is hurting and why the work… → Hypothesis: the causal bet behind the… → Product Summary: what should exist when… → …
  • Changing work governed by a Product Spec
  • SKILL.md covers How To Use A Product Spec, Planning Rules, Change Rules and Output Rules
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Productspec is an agent skill from gokulrajaram/ProductSpec. Use when implementing, reviewing, planning, or changing work governed by a Product Spec. Treat .product-spec.md files as the product contract for the work.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Product & Project Management, covering PRD writing. The repository describes itself as: Open standard for software intent in the AI agent era. The licence is MIT.

When your agent uses it

  • Changing work governed by a Product Spec
  • Tasks that involve PRD writing

Example prompts

  • “/productspec”

Workflow steps

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

  1. Problem: who is hurting and why the work matters.
  2. Hypothesis: the causal bet behind the product.
  3. Product Summary: what should exist when the work is done.
  4. Scope: what is in, out, and deliberately cut.
  5. Acceptance Criteria: the build contract, including AI evals when present.
  6. Success Metrics: post-launch outcome checks.
  7. Related Artifacts: issues, pull requests, eval runs, dashboards, designs, engineering specs, or other Product Specs the work depends on.

What it can do on your machine

Read from SKILL.md and the folder at commit 97b90b6. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    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

Productspec loads about 1.3k tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 727 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~42
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

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 gokulrajaram/ProductSpec at commit 97b90b6, republished under its MIT licence (© gokulrajaram). 727 words, ~1,286 tokens.

Download SKILL.mdSave it as .claude/skills/productspec/SKILL.md (or your agent's skills folder).
name
productspec
description
Use when implementing, reviewing, planning, or changing work governed by a Product Spec. Treat `.product-spec.md` files as the product contract for the work.

ProductSpec Agent Skill

Product Specs are the product contract for consequential software work.

When a repo uses Agent Run files, treat them as the receipt for one agent execution against a pinned Product Spec revision.

Before planning, coding, testing, or changing scope, look for relevant .product-spec.md files in the repository. Common locations include:

  • specs/
  • product-specs/
  • docs/product-specs/
  • paths named in the task, issue, pull request, or engineering spec

If a relevant Product Spec exists, read it before acting.

How To Use A Product Spec

Read these sections in order:

  1. Problem: who is hurting and why the work matters.
  2. Hypothesis: the causal bet behind the product.
  3. Product Summary: what should exist when the work is done.
  4. Scope: what is in, out, and deliberately cut.
  5. Acceptance Criteria: the build contract, including AI evals when present.
  6. Success Metrics: post-launch outcome checks.
  7. Related Artifacts: issues, pull requests, eval runs, dashboards, designs, engineering specs, or other Product Specs the work depends on.

Acceptance Criteria are the build contract. Plans, tasks, code changes, tests, and pull request summaries should cite the relevant AC-<number> IDs.

AI evals are pre-launch gates inside Acceptance Criteria, not a separate ## AI Evals section. Cite EVAL-<number> when implementing or changing model behavior.

Success Metrics are post-launch outcomes. Do not treat SM-<number> items as implementation tasks.

Planning Rules

When creating an implementation plan:

  • List which Product Spec and spec_revision you are implementing.
  • If ProductSpec MCP is available, call begin_spec_session before planning and include the returned spec_revision and session id in your plan.
  • Map each task to the relevant Acceptance Criteria.
  • Name any Acceptance Criteria that are not covered by the plan.
  • Treat scope.out and scope.cut as explicit non-goals.
  • Use applies_to and Related Artifacts to find relevant code, issues, pull requests, designs, evals, and dashboards.
  • Resolve product_spec related artifacts before planning. A spec whose depends_on target is not built yet is blocked, not buildable, and the plan should say what it waits for.
  • For a folder of specs, run productspec graph <dir> --json (or the get_spec_graph MCP tool) to get the buildable set, the blocked set with what each spec waits for, and a dependency-respecting build order in one call, instead of re-reading every spec to derive it.
  • For a repo with Product Specs, Agent Runs, Decision Traces, and evidence links, run productspec garden <repo> --json before selecting work. Use it to find missing evidence, stale revision pins, run gaps, Decision Trace gaps, unscoped specs, contention, and waves.
  • If another agent may be working the same folder, read contention and waves from that same call. Two specs that touch one surface must not be built at the same time, even when both are buildable. Take work from the current wave, and treat a spec listed in unscoped as unknown scope rather than safe scope.
  • Treat RESOLVE-IN-PLAN: markers as unresolved technical bindings. Resolve each marker against the codebase with a source citation before coding.
  • Do not implement guessed table names, fields, endpoints, services, or file paths as if they were binding instructions.
Show full SKILL.md (224 more words)Show less

Change Rules

Do not silently change product intent.

If implementation pressure conflicts with the Product Spec, state the conflict and propose one of:

  • update the Product Spec
  • update the implementation
  • accept a tradeoff and record a Decision Trace
  • reopen the work

If behavior changes after implementation, propose a Product Spec revision or a Decision Trace entry instead of treating code drift as intent.

Output Rules

When reporting progress or opening a pull request:

  • If ProductSpec MCP is available, call check_spec_session first. If the Product Spec changed, re-read it and re-plan before claiming done.
  • If ProductSpec MCP is available, call get_evidence_checklist and attach or name evidence for covered AC- and EVAL- IDs.
  • If the repo uses Agent Run files, call draft_agent_run or run productspec init-run <spec> <agent-run> to create a receipt, then fill in checked AC-, EVAL-, and SM- IDs, evidence links, drift state, and completion claim. Validate it with productspec validate-run.
  • Before claiming completion, run productspec reconcile <spec> --against <agent-run> when a local CLI is available. Fix missing checked items, failed items, stale spec revisions, passed items without evidence, or drift without Decision Trace before saying the work is done.
  • cite the Product Spec path and spec_revision
  • cite the Acceptance Criteria covered
  • cite AI evals added or changed
  • name scope items intentionally deferred
  • link related issues, pull requests, eval runs, or dashboards when available

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

Files

Just SKILL.md in skills/productspec of gokulrajaram/ProductSpec.

Open the folder on GitHubat commit 97b90b6

Compare with similar skills

Productspec 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.

Productspec compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Productspec this skillgokulrajaram/ProductSpec306—~1.3kAutomated safety check: PassMIT
CCPM Project Managementautomazeio/ccpm8.4k—~1.1kAutomated safety check: PassMIT
To Issuesywwynm/EverythingDone14412 repos~893Automated safety check: PassGPL-3.0
ArchitectHainrixz/the-architect537—~3.6kAutomated safety check: PassMIT
Schematicblader/schematic241—~2.2kAutomated safety check: PassMIT
Design Decknicobailon/pi-design-deck292—~4.3kAutomated safety check: PassNone

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  • To Issues

    ywwynm/EverythingDone

    Break a plan, spec, or PRD into independently-grabbable issues on the project issue tracker using tracer-bullet vertical slices.

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More from gokulrajaram/ProductSpec

  • Productspec Authoring

    gokulrajaram/ProductSpec

    Writes, validates, and converts ProductSpec files (.product-spec.md), the Markdown format for recording product intent before implementation.

    306 GitHub stars~929 tokensUpdated 2 mo ago
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Categories

Questions about Productspec

What does Productspec do?

A skill your agent uses when implementing, reviewing, planning, or changing work governed by a Product Spec. Productspec is an agent skill from gokulrajaram/ProductSpec. Use when implementing, reviewing, planning, or changing work governed by a Product Spec.

When should I use Productspec?

Productspec fits situations like: changing work governed by a Product Spec; tasks that involve PRD writing.

How do I install Productspec in Claude Code?

Run `npx skills add gokulrajaram/ProductSpec --skill productspec -a claude-code`. Or copy the skill folder (skills/productspec in gokulrajaram/ProductSpec) into .claude/skills/productspec in your project. Claude Code loads it when a task matches its description.

How do I install Productspec in Codex?

Run `npx skills add gokulrajaram/ProductSpec --skill productspec -a codex`. Or copy the skill folder (skills/productspec in gokulrajaram/ProductSpec) into .agents/skills/productspec in your project. Codex loads it when a task matches its description.

Can I use Productspec 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 gokulrajaram/ProductSpec --skill productspec -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/productspec, .gemini/skills/productspec, .github/skills/productspec and .opencode/skills/productspec in your project.

What does Productspec need to run?

SKILL.md names no scripts, command-line tools or credentials: Productspec is instructions for the agent only.

Does Productspec 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 Productspec 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 Productspec use?

Productspec 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 Productspec use?

About 1.3k tokens (SKILL.md is roughly 5.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Productspec?

Skills that share tags, products or a category with Productspec: CCPM Project Management (automazeio/ccpm, 8.4k stars), To Issues (ywwynm/EverythingDone, 144 stars), Architect (Hainrixz/the-architect, 537 stars) and Schematic (blader/schematic, 241 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Productspec?

gokulrajaram (a GitHub user) maintains it in gokulrajaram/ProductSpec, which has 306 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on July 19, 2026.

Source: gokulrajaram/ProductSpec on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.