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Agent skill

Spec To Repo

by borghei in borghei/Claude-Skills

Translate product specs (PRDs, user stories) into a ship-ready repo plan: ticket decomposition, branch strategy, and PR sequencing.

MITAuto-check passedProduct & Project Management

Install Spec To Repo

skills CLI
$ npx skills add borghei/Claude-Skills --skill spec-to-repo -a claude-code

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

GitHub CLI
$ gh skill install borghei/Claude-Skills spec-to-repo --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/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/product-team/spec-to-repo .claude/skills/spec-to-repo && 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
spec-to-repo
GitHub stars
891
Token cost
~1.9k tokens
SKILL.md length
886 words
Files
7 (incl. scripts, references)
Skills in repo
354
Repo updated
First seen
Licence
MIT

At a glance

Translate product specs (PRDs, user stories) into a ship-ready repo plan: ticket decomposition, branch strategy, and PR sequencing.

  • Works in 3 steps: Pull the PRD; identify the user-facing… → Run prd_to_tickets_decomposer.py with… → Manually review; tune for team-specific…
  • Breaking a PRD into tickets
  • SKILL.md covers When to use this skill, Inputs the advisor expects, Clarify First and Workflows, plus 5 more sections
  • Runs Python scripts from its folder; calls python3 and git

What it does

Spec To Repo is an agent skill from borghei/Claude-Skills. Translate product specs (PRDs, user stories) into a ship-ready repo plan: ticket decomposition, branch strategy, and PR sequencing. Use when breaking a PRD into tickets or designing the branch/PR sequence.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `references/branch-strategy-for-features.md`, `references/pr-discipline-and-conventions.md` and `references/spec-to-ticket-decomposition.md`).

It sits in Product & Project Management, covering PRD writing and User stories. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.

When your agent uses it

  • Breaking a PRD into tickets
  • Designing the branch/PR sequence

Example prompts

  • “/spec-to-repo”

Requirements

  • Python 3

Workflow steps

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

  1. Pull the PRD; identify the user-facing capabilities.
  2. Run prd_to_tickets_decomposer.py with the user stories + technical
  3. Manually review; tune for team-specific patterns.

What it can do on your machine

Read from SKILL.md and the folder at commit 4a698e8. 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

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3
    • git

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

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    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

Spec To Repo loads about 1.9k tokens when it runs, and up to ~7.1k if it reads all its reference files. Until then it costs about 55 tokens; SKILL.md has 886 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~55
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
~7.1k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from borghei/Claude-Skills at commit 4a698e8, republished under its MIT licence (© borghei). 886 words, ~1,943 tokens.

Download SKILL.mdSave it as .claude/skills/spec-to-repo/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
spec-to-repo
description
Translate product specs (PRDs, user stories) into a ship-ready repo plan: ticket decomposition, branch strategy, and PR sequencing. Use when breaking a PRD into tickets or designing the branch/PR sequence.
license
MIT + Commons Clause
metadata.version
1.0.0
metadata.author
borghei
metadata.category
product-team
metadata.domain
delivery
metadata.updated
2026-05-27
metadata.tags
prd, ticket-decomposition, branch-strategy, pr, definition-of-done, delivery

Spec to Repo

A delivery-focused skill that bridges product spec to repository work. Where PRD-writing skills focus on what to build, this skill focuses on how to break it down for execution — the ticket decomposition, branch strategy, PR sequencing, and acceptance criteria that make a spec actually ship.

When to use this skill

  • Translating a PRD or feature brief into a sequence of tickets
  • Designing the branch + PR sequence for a multi-week feature
  • Auditing an existing ticket decomposition for risk (big tickets, hidden dependencies)
  • Defining definition-of-done that covers code, tests, docs, telemetry
  • Planning incremental shipping (feature flags, canaries, dark-launch)
  • Reviewing a decomposition before sprint planning to avoid mid-sprint surprises

Inputs the advisor expects

  • The PRD or spec document
  • Target ship window (1 sprint? 1 month? 1 quarter?)
  • Engineering team size + composition (FE, BE, ML, mobile)
  • Risk profile (greenfield vs production-impacting)
  • Feature-flag and rollout posture

Clarify First

Before generating the repo plan, confirm these inputs. If any is unknown or vague, ASK — do not assume:

  • The PRD or spec — the user-facing capabilities to decompose (drives the epic→ticket tree)
  • Target ship window — one sprint, month, or quarter (drives ticket sizing and PR sequencing)
  • Team composition — FE, BE, ML, mobile (decides parallel paths and vertical-slice tickets)
  • Feature-flag and rollout posture — flagged/dark-launch vs direct ship (drives PR sequencing and definition-of-done)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Workflows

Workflow 1 — Decompose a PRD into tickets
  1. Pull the PRD; identify the user-facing capabilities.
  2. Run prd_to_tickets_decomposer.py with the user stories + technical notes to surface a candidate ticket tree (epic → tickets → subtasks) with size estimates and dependencies.
  3. Manually review; tune for team-specific patterns.
bash
python3 spec-to-repo/scripts/prd_to_tickets_decomposer.py \
  --input prd.json --format markdown
Workflow 2 — Validate the branch and PR plan
  1. Capture proposed branch + PR sequence.
  2. Run pr_scope_analyzer.py to flag oversized PRs, missing tests, missing telemetry, and risky merges.
  3. Adjust before opening PRs.
bash
python3 spec-to-repo/scripts/pr_scope_analyzer.py \
  --input pr_plan.json --format markdown
Workflow 3 — Lint branch names against convention
  1. Capture branch list (e.g., git branch --list).
  2. Run branch_naming_validator.py to flag non-conformant names.
bash
python3 spec-to-repo/scripts/branch_naming_validator.py \
  --input branches.txt --format markdown

Decision frameworks

Ticket sizing
SizeEffortDescription
XS< 0.5 dayTrivial; usually skip ticketing
S0.5–1 dayOne simple change
M1–3 daysSingle feature, well-scoped
L3–5 daysMulti-day work; should split if possible
XL> 5 daysAlways split — too big for confident estimate

A ticket that's L or XL almost always hides a missing decomposition. Push back on yourself.

The ticket tree
Epic — large product feature ("Notifications v2")
├── Story — user-facing capability ("As a user I can mute by channel")
│   ├── Ticket — one engineering work item (backend, frontend, infra)
│   │   └── Subtask — atomic step (optional)

Most orgs:

  • Epic ≈ PRD-sized scope
  • Story ≈ one user-facing slice
  • Ticket ≈ one PR (or pair of PRs: BE + FE)
The "vertical slice"

Best ticket: ships a small user-visible improvement end-to-end.

  • Backend change + frontend change + tests + telemetry + docs in one ship
  • Better than: BE-only ticket waiting for FE-only ticket waiting for QA

When you can't slice vertically (e.g., backend is weeks before frontend):

  • Use feature flags to ship behind a switch
  • Dark-launch backend to validate before frontend
  • Communicate the lag explicitly
PR sequencing

For a multi-PR feature:

  1. PR 1 — Infrastructure / scaffolding (no behavior change)
  2. PR 2 — Backend changes (behind flag; no frontend uses it)
  3. PR 3 — Frontend changes (behind flag; tests pass with flag on/off)
  4. PR 4 — Telemetry + analytics events
  5. PR 5 — Documentation + runbook
  6. PR 6 — Flag enablement (small change; reviewable cleanly)

Each PR < 400 lines if possible. Reviewability collapses above 400.

Show full SKILL.md (330 more words)Show less
Definition of done

Per ticket:

  • Code: written, reviewed, merged
  • Tests: unit + integration as appropriate
  • Telemetry: events fired (and verified)
  • Docs: README / runbook / API doc updated as needed
  • Accessibility: meets the project bar
  • Feature flag: configured (if applicable)
  • Rollout plan: defined for non-flagged ships

Per epic:

  • All tickets complete
  • Feature behind flag in production for 1+ week (if risky)
  • Flag enabled for X% (canary), then ramped
  • Telemetry shows expected behavior
  • Customer-facing comms drafted (if applicable)

Common engagements

"Help me decompose this PRD"
  1. List user-facing capabilities (1-line each).
  2. For each, list the backend, frontend, infra, telemetry, docs work.
  3. Estimate; flag anything > 3 days for further breakdown.
  4. Sequence: scaffolding first, behavior next, flag enablement last.
  5. Identify cross-team dependencies; engage before sprint start.
"Our team is shipping huge PRs"
  1. Audit the last 10 PRs: median size, P95 size.
  2. Identify the patterns: monolithic services + flag-less work + slow review.
  3. Pilot: feature flags + ticket-first decomposition + PR size SLA.
  4. Track: median PR size + lead time week-over-week.
"Help me plan the rollout"
  1. Define a successful launch criterion (e.g., < 0.5% error rate at 50%).
  2. Identify the kill switch (feature flag or quick-revert).
  3. Plan ramps: 1% → 5% → 25% → 50% → 100% with bake time.
  4. Define rollback criteria + comms plan.
  5. Coordinate with on-call + support.

Anti-patterns to avoid

  • Decomposition as wishful thinking. "3-day estimate" with no break-down is a 2-week-actual.
  • Sequential ticket tree (everyone waits). Plan parallel paths.
  • Hidden dependencies on other teams. Surface them in decomposition.
  • No feature flag. Shippable in chunks but every change goes to all users immediately.
  • PRs > 1000 lines. Reviewability dies; bugs hide.
  • DoD that's just "code merged." Forgets tests, docs, telemetry.
  • Ticket = a day of work. Sometimes tickets are 30 minutes; sometimes 3 days.

References

  • references/spec-to-ticket-decomposition.md — patterns for breaking specs into tickets
  • references/branch-strategy-for-features.md — branching, feature flags, dark-launch
  • references/pr-discipline-and-conventions.md — PR size, review, definition-of-done
  • product-team/agile-product-owner — sprint planning, prioritization
  • engineering/feature-flags-architect — flag strategy
  • engineering/observability-designer — SLO / telemetry
  • c-level-advisor/vpe-advisor — broader delivery context
  • project-management/ skills — ticket / sprint management tooling

© borghei, 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 6 other files (scripts, references) in product-team/spec-to-repo of borghei/Claude-Skills.

  • SKILL.md
  • references/branch-strategy-for-features.md
  • references/pr-discipline-and-conventions.md
  • references/spec-to-ticket-decomposition.md
  • scripts/branch_naming_validator.py
  • scripts/pr_scope_analyzer.py
  • scripts/prd_to_tickets_decomposer.py

Open the folder on GitHubat commit 4a698e8

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Categories

Questions about Spec To Repo

What does Spec To Repo do?

Translate product specs (PRDs, user stories) into a ship-ready repo plan: ticket decomposition, branch strategy, and PR sequencing. Spec To Repo is an agent skill from borghei/Claude-Skills. Translate product specs (PRDs, user stories) into a ship-ready repo plan: ticket decomposition, branch strategy, and PR sequencing.

When should I use Spec To Repo?

Spec To Repo fits situations like: breaking a PRD into tickets; designing the branch/PR sequence.

How do I install Spec To Repo in Claude Code?

Run `npx skills add borghei/Claude-Skills --skill spec-to-repo -a claude-code`. Or copy the skill folder (product-team/spec-to-repo in borghei/Claude-Skills) into .claude/skills/spec-to-repo in your project. Claude Code loads it when a task matches its description.

How do I install Spec To Repo in Codex?

Run `npx skills add borghei/Claude-Skills --skill spec-to-repo -a codex`. Or copy the skill folder (product-team/spec-to-repo in borghei/Claude-Skills) into .agents/skills/spec-to-repo in your project. Codex loads it when a task matches its description.

Can I use Spec To Repo 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 borghei/Claude-Skills --skill spec-to-repo -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/spec-to-repo, .gemini/skills/spec-to-repo, .github/skills/spec-to-repo and .opencode/skills/spec-to-repo in your project.

What does Spec To Repo need to run?

Going by SKILL.md and its folder, Spec To Repo needs Python for the scripts in its folder and the command-line tools its instructions call (python3 and git). Our summary lists: Python 3.

Does Spec To Repo access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Spec To Repo 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Spec To Repo use?

Spec To Repo is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Spec To Repo use?

About 1.9k tokens (SKILL.md is roughly 7.8k 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 5.2k tokens, read only when the agent opens those files.

What are the alternatives to Spec To Repo?

Skills that share tags, products or a category with Spec To Repo: Ralph Tui Create Beads (subsy/ralph-tui, 2.5k stars), Ralph Tui Create Beads Rust (subsy/ralph-tui, 2.5k stars), Ralph Tui Create JSON (subsy/ralph-tui, 2.5k stars) and To Prd (ywwynm/EverythingDone, 144 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Spec To Repo?

borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 891 GitHub stars. The repository holds 354 skills in this directory. The repository was last updated on October 7, 2026.

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