Run Jira
DataDog/datadog-agent
Fetch a Jira issue and propose an implementation plan based on codebase analysis
Creates a comprehensive, context-rich implementation plan through deep codebase analysis, a short clarifying interview, and external research.
$ npx skills add coleam00/skills --skill piv-plan-implementation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install coleam00/skills piv-plan-implementation --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/coleam00/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/piv-plan-implementation .claude/skills/piv-plan-implementation && rm -rf skills-srcUse ~/.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/
Install the "piv-plan-implementation" agent skill from https://github.com/coleam00/skills/tree/main/.claude/skills/piv-plan-implementation into .claude/skills/piv-plan-implementation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "piv-plan-implementation", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/coleam00/skills/tree/main/.claude/skills/piv-plan-implementationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add coleam00/skills --skill piv-plan-implementation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install coleam00/skills piv-plan-implementation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coleam00/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/piv-plan-implementation .agents/skills/piv-plan-implementation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "piv-plan-implementation" agent skill from https://github.com/coleam00/skills/tree/main/.claude/skills/piv-plan-implementation into .agents/skills/piv-plan-implementation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "piv-plan-implementation", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add coleam00/skills --skill piv-plan-implementation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install coleam00/skills piv-plan-implementation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coleam00/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/piv-plan-implementation .cursor/skills/piv-plan-implementation && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "piv-plan-implementation" agent skill from https://github.com/coleam00/skills/tree/main/.claude/skills/piv-plan-implementation into .cursor/skills/piv-plan-implementation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "piv-plan-implementation", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/coleam00/skills.git --path .claude/skills/piv-plan-implementation--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add coleam00/skills --skill piv-plan-implementation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install coleam00/skills piv-plan-implementation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coleam00/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/piv-plan-implementation .gemini/skills/piv-plan-implementation && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "piv-plan-implementation" agent skill from https://github.com/coleam00/skills/tree/main/.claude/skills/piv-plan-implementation into .gemini/skills/piv-plan-implementation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "piv-plan-implementation", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install coleam00/skills piv-plan-implementationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add coleam00/skills --skill piv-plan-implementation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/coleam00/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/piv-plan-implementation .github/skills/piv-plan-implementation && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "piv-plan-implementation" agent skill from https://github.com/coleam00/skills/tree/main/.claude/skills/piv-plan-implementation into .github/skills/piv-plan-implementation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "piv-plan-implementation", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add coleam00/skills --skill piv-plan-implementation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install coleam00/skills piv-plan-implementation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coleam00/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/piv-plan-implementation .opencode/skills/piv-plan-implementation && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "piv-plan-implementation" agent skill from https://github.com/coleam00/skills/tree/main/.claude/skills/piv-plan-implementation into .opencode/skills/piv-plan-implementation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "piv-plan-implementation", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
piv-plan-implementationCreates a comprehensive, context-rich implementation plan through deep codebase analysis, a short clarifying interview, and external research.
Piv Plan Implementation is an agent skill from coleam00/skills. Creates a comprehensive, context-rich implementation plan through deep codebase analysis, a short clarifying interview, and external research. Accepts a tracker ticket (a Jira/Linear/GitHub key or URL, fetched from the tracker) or a free-form feature request. Use when you have a ticket or feature and need a one-pass-ready plan before writing any code.
Its SKILL.md is about 4.9k 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 Agent Workflows, covering Planning and Codebase onboarding. It works with GitHub and Jira. The repository describes itself as: The agent skills I actually use to build software with coding agents. The PIV loop, planning, worktrees, and the meta-skills for building your own AI Layer. The licence is MIT.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 847be08. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
ghFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use gh, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Piv Plan Implementation loads about 4.9k tokens when it runs. Until then it costs about 94 tokens; SKILL.md has 1,334 words of instructions outside code blocks.
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.
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.
The full file from coleam00/skills at commit 847be08, republished under its MIT licence (© coleam00). 1,334 words, ~4,905 tokens.
.claude/skills/piv-plan-implementation/SKILL.md (or your agent's skills folder).$ARGUMENTS is either a tracker ticket (a key like ACC-30, or a Jira / Linear / GitHub issue URL) or a
free-form feature description. Tell them apart and handle each:
ABC-123, or an issue URL): fetch it from the tracker before you plan (Jira via
the Atlassian MCP, GitHub via gh issue view, etc.). Read its summary, acceptance criteria, and per-ticket
context. Then follow its links up to the epic and the epic's linked architecture page (Confluence via the
Atlassian MCP) and inherit those decisions (see "Inherit, don't re-decide" below). Never plan from the bare key;
the ticket body plus its epic and architecture are the real input.Transform a feature request into a comprehensive implementation plan through systematic codebase analysis, external research, and strategic planning.
Core Principle: We do NOT write code in this phase. Our goal is to create a context-rich implementation plan that enables one-pass implementation success for ai agents.
Key Philosophy: Context is King. The plan must contain ALL information needed for implementation - patterns, mandatory reading, documentation, validation commands - so the execution agent succeeds on the first attempt.
Inherit, don't re-decide: This is a per-ticket plan. If the ticket belongs to an epic that already has architecture decisions — a linked architecture page (e.g. a Confluence page from the plan-architecture skill, reached from the ticket's epic), an ## Architecture / ## Engineering section on the epic, or a local architecture.md / engineering-plan.md — read it first and treat its cross-cutting calls (stack & versions, data model, security boundaries, the seams new code plugs into) as already decided. Inherit them; don't reopen them. Plan only what's left at the ticket level: the specific files, the local patterns to mirror, the tests. If a ticket genuinely needs to break an epic-level decision, flag it in Open Questions rather than silently diverging.
Deep Feature Analysis:
Create User Story Format Or Refine If Story Was Provided By The User:
As a <type of user>
I want to <action/goal>
So that <benefit/value>Use specialized agents and parallel analysis:
1. Project Structure Analysis
2. Pattern Recognition (Use specialized subagents when beneficial)
3. Dependency Analysis
4. Testing Patterns
5. Integration Points
Clarify Ambiguities — GATE:
Codebase analysis is done, so the open questions are now specific. This is the one moment where you know enough to ask well and have not yet written anything. GATE means: post the questions, then stop. End the turn and wait for the answers. Do not ask and answer in the same breath, and do not roll into Phase 3.
Ask in one cluster, numbered, 3-6 questions max, each carrying a recommended default so answering is cheap ("I'll mirror the first unless you say otherwise"). Draw them only from what the analysis actually left open:
file:line and ask which to mirror.Skip any category with nothing genuinely open; never manufacture questions to fill the list. If the ticket, its epic and the architecture doc genuinely settle everything, say so in one line and proceed. Silence is not the same as clearance.
Thin answers: reflect a vague answer back as the concrete choice it leaves open ("'handle errors gracefully' — a 4xx with a message, or retry then 503?") and ask once more. Never upgrade a vague answer into a confident plan.
If they decline ("just write it"): honour it, but name what you are guessing. Every unanswered item becomes
an Assumed — <the assumption>, confirm before execution line in OPEN QUESTIONS / ASSUMPTIONS, and the task it
affects carries a **GOTCHA** naming it. Never guess silently.
Already settled upstream: anything the ticket, its epic, or the linked architecture page already answers is not open. Inherit it and skip (see "Inherit, don't re-decide").
Use specialized subagents when beneficial for external research:
Documentation Gathering:
Technology Trends:
Compile Research References:
## Relevant Documentation
- [Library Official Docs](https://example.com/docs#section)
- Specific feature implementation guide
- Why: Needed for X functionality
- [Framework Guide](https://example.com/guide#integration)
- Integration patterns section
- Why: Shows how to connect componentsThink Harder About:
Design Decisions:
Create comprehensive plan with the following structure:
Whats below here is a template for you to fill for the implementation agent:
# Feature: <feature-name>
The following plan should be complete, but its important that you validate documentation and codebase patterns and task sanity before you start implementing.
Pay special attention to naming of existing utils types and models. Import from the right files etc.
## Feature Description
<Detailed description of the feature, its purpose, and value to users>
## User Story
As a <type of user>
I want to <action/goal>
So that <benefit/value>
## Problem Statement
<Clearly define the specific problem or opportunity this feature addresses>
## Solution Statement
<Describe the proposed solution approach and how it solves the problem>
## Out of Scope / Non-Goals
<Explicitly bound the work: what this feature does NOT include. Name the things a reasonable reader might assume are in scope but aren't — this is what stops the agent from gold-plating or solving the wrong problem.>
- Not included: <thing> (defer to <later / separate ticket>)
- Not changing: <existing behavior to leave alone>
## Feature Metadata
**Feature Type**: [New Capability/Enhancement/Refactor/Bug Fix]
**Estimated Complexity**: [Low/Medium/High]
**Primary Systems Affected**: [List of main components/services]
**Dependencies**: [External libraries or services required]
## Related Work
<Links between this plan and the work around it. Distinct from CONTEXT REFERENCES below (which lists files/docs to read for *this* implementation) — this is the plan's place in the larger graph.>
**Implements**: <ticket id / link> · **Epic**: <engineering-plan.md path or epic link — if this ticket inherits an epic's engineering plan (see Mission), record it here>
**Back-references** (plans this builds on or inherits decisions from):
- `.claude/plans/<prior-plan>.md` - Why: shares the auth seam / reuses the X service
**Forward-references** (plans that extend or supersede this — append as follow-ups get created):
- (none yet)
---
## CONTEXT REFERENCES
### Relevant Codebase Files IMPORTANT: YOU MUST READ THESE FILES BEFORE IMPLEMENTING!
<List files with line numbers and relevance>
- `path/to/file.py` (lines 15-45) - Why: Contains pattern for X that we'll mirror
- `path/to/model.py` (lines 100-120) - Why: Database model structure to follow
- `path/to/test.py` - Why: Test pattern example
### New Files to Create
- `path/to/new_service.py` - Service implementation for X functionality
- `path/to/new_model.py` - Data model for Y resource
- `tests/path/to/test_new_service.py` - Unit tests for new service
### Relevant Documentation YOU SHOULD READ THESE BEFORE IMPLEMENTING!
- [Documentation Link 1](https://example.com/doc1#section)
- Specific section: Authentication setup
- Why: Required for implementing secure endpoints
- [Documentation Link 2](https://example.com/doc2#integration)
- Specific section: Database integration
- Why: Shows proper async database patterns
### Patterns to Follow
<Specific patterns extracted from codebase - include actual code examples from the project>
**Naming Conventions:** (for example)
**Error Handling:** (for example)
**Logging Pattern:** (for example)
**Other Relevant Patterns:** (for example)
---
## IMPLEMENTATION PLAN
Phases run **top to bottom by default** — each assumes the phase above it is done. Where that is NOT the true dependency, make it explicit with a `**Depends on:**` line under the phase header, and a `**Independent of:**` line where two phases don't block each other. Independent phases are candidates to run in **parallel** (e.g. separate worktrees / parallel loops). Only annotate where it changes execution order or unlocks parallelism — skip the obvious sequential case.
### Phase 1: Foundation
<Describe foundational work needed before main implementation>
**Tasks:**
- Set up base structures (schemas, types, interfaces)
- Configure necessary dependencies
- Create foundational utilities or helpers
### Phase 2: Core Implementation
**Depends on:** Phase 1 (needs the base schemas/types)
<Describe the main implementation work>
**Tasks:**
- Implement core business logic
- Create service layer components
- Add API endpoints or interfaces
- Implement data models
### Phase 3: Integration
<Describe how feature integrates with existing functionality>
**Tasks:**
- Connect to existing routers/handlers
- Register new components
- Update configuration files
- Add middleware or interceptors if needed
### Phase 4: Testing & Validation
<Describe testing approach>
**Tasks:**
- Implement unit tests for each component
- Create integration tests for feature workflow
- Add edge case tests
- Validate against acceptance criteria
---
## STEP-BY-STEP TASKS
IMPORTANT: Execute every task in order, top to bottom. Each task is atomic and independently testable.
### Task Format Guidelines
Use information-dense keywords for clarity:
- **CREATE**: New files or components
- **UPDATE**: Modify existing files
- **ADD**: Insert new functionality into existing code
- **REMOVE**: Delete deprecated code
- **REFACTOR**: Restructure without changing behavior
- **MIRROR**: Copy pattern from elsewhere in codebase
### {ACTION} {target_file}
- **IMPLEMENT**: {Specific implementation detail}
- **PATTERN**: {Reference to existing pattern - file:line}
- **IMPORTS**: {Required imports and dependencies}
- **GOTCHA**: {Known issues or constraints to avoid}
- **VALIDATE**: `{executable validation command}`
- **SATISFIES**: {which acceptance criterion this task advances — e.g. AC #2 — so every task traces to a criterion}
<Continue with all tasks in dependency order...>
---
## TESTING STRATEGY
<Define testing approach based on project's test framework and patterns discovered during research>
### Unit Tests
<Scope and requirements based on project standards>
Design unit tests with fixtures and assertions following existing testing approaches
### Integration Tests
<Scope and requirements based on project standards>
### Edge Cases
<List specific edge cases that must be tested for this feature>
---
## VALIDATION COMMANDS
<Define validation commands based on project's tools discovered in Phase 2>
Execute every command to ensure zero regressions and 100% feature correctness.
### Level 1: Syntax & Style
<Project-specific linting and formatting commands>
### Level 2: Unit Tests
<Project-specific unit test commands>
### Level 3: Integration Tests
<Project-specific integration test commands>
### Level 4: Manual Validation
<Feature-specific manual testing steps - API calls, UI testing, etc.>
### Level 5: Additional Validation (Optional)
<MCP servers or additional CLI tools if available>
---
## ACCEPTANCE CRITERIA
<List specific, measurable criteria that must be met for completion>
- [ ] Feature implements all specified functionality
- [ ] All validation commands pass with zero errors
- [ ] Unit test coverage meets requirements (80%+)
- [ ] Integration tests verify end-to-end workflows
- [ ] Code follows project conventions and patterns
- [ ] No regressions in existing functionality
- [ ] Documentation is updated (if applicable)
- [ ] Performance meets requirements (if applicable)
- [ ] Security considerations addressed (if applicable)
---
## COMPLETION CHECKLIST
- [ ] All tasks completed in order
- [ ] Each task validation passed immediately
- [ ] All validation commands executed successfully
- [ ] Full test suite passes (unit + integration)
- [ ] No linting or type checking errors
- [ ] Manual testing confirms feature works
- [ ] Acceptance criteria all met
- [ ] Code reviewed for quality and maintainability
---
## OPEN QUESTIONS / ASSUMPTIONS
<Surface anything still uncertain instead of silently guessing. List the assumptions this plan makes, and any question that — if answered differently — would change the plan. Flag unresolved critical questions for the user before execution.>
## NOTES (open canvas)
<No fixed shape. Reason freely here: alternatives you weighed and rejected and why, a tradeoff matrix, a sequencing or rollout risk, a data-flow sketch, open threads, links — whatever serves the plan. The sections above template the plan's *shape* so the trifecta and the implementation agent can consume it; this section keeps your *reasoning* unconstrained. Prose, lists, tables, code blocks all welcome.>
## AMENDMENTS
<Append-only history of changes made to this plan AFTER it was first approved/executed. Leave empty at creation; newest entry at the bottom. Each entry: date — what changed and why.>
- <ISO date> — <what changed and why, e.g. "scope cut: deferred bulk-import to a follow-up ticket after AC review">Filename: .claude/plans/{kebab-case-descriptive-name}.md
{kebab-case-descriptive-name} with short, descriptive feature nameadd-user-authentication.md, implement-search-api.md, refactor-database-layer.mdDirectory: Create .claude/plans/ if it doesn't exist
One-Pass Implementation: Execution agent can complete feature without additional research or clarification — clarification the user owes the plan belongs in Phase 2's gate, not deferred to the execution agent
Validation Complete: Every task has at least one working validation command
Context Rich: The Plan passes "No Prior Knowledge Test" - someone unfamiliar with codebase can implement using only Plan content
Confidence Score: #/10 that execution will succeed on first attempt
After creating the Plan, provide:
© coleam00, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .claude/skills/piv-plan-implementation of coleam00/skills.
Open the folder on GitHubat commit 847be08
Piv Plan Implementation 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Piv Plan Implementation this skillcoleam00/skills | 670 | — | ~4.9k | Automated safety check: Pass | MIT | |
| Run JiraDataDog/datadog-agent | 3.8k | — | ~635 | Automated safety check: Pass | Apache-2.0 | |
| PRP Implementation PlannerWirasm/prp | 2.3k | — | ~4.1k | Automated safety check: Pass | MIT | |
| PRP PlanWirasm/prp | 2.3k | — | ~4k | Automated safety check: Pass | MIT | |
| sfdx-hardis Architecture Guidehardisgroupcom/sfdx-hardis | 401 | — | ~2.1k | Automated safety check: Pass | AGPL-3.0 | |
| Repomix Codebase Packeryamadashy/repomix | 29k | — | ~1.3k | Automated safety check: Notes | MIT |
DataDog/datadog-agent
Fetch a Jira issue and propose an implementation plan based on codebase analysis
Wirasm/prp
Turns a PRD, issue or description into an implementation-ready plan grounded in codebase evidence, adding root-cause analysis for bugs and publishing issue plans back to the issue.
Wirasm/prp
Writes an implementation-ready plan for a feature, bug fix, refactor or chore from a PRD, issue or description, grounded in codebase evidence, and can post it back to the source issue.
hardisgroupcom/sfdx-hardis
Explains how the sfdx-hardis Salesforce CLI plugin is built: its TypeScript and Oclif stack, command layout, agent-mode flag and provider classes for git, notifications and AI.
yamadashy/repomix
Packs a local directory or remote GitHub repository into one AI-friendly file with Repomix, then searches it to explore structure, find patterns and count tokens.
Yeachan-Heo/oh-my-claudecode
Charts a foggy effort into a map of decision tickets on the repo's issue tracker and works through them one per session, producing decisions rather than deliverables.
coleam00/skills
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coleam00/skills
Take a PRD and build a dark factory around it - a repository that takes work in as an issue and ships validated code out with nobody at the keyboard - one component at a time, into the user's actual…
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Take real control of the desktop - list and focus windows, type, paste, click, scroll, and screenshot - on Windows, macOS or Linux, and drive other coding-agent sessions running in terminals.
coleam00/skills
Audit any second brain, notes folder, or agent memory for facts that have quietly stopped being true, then fix the worst one so it stops recurring.
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Build a personal signal engine from scratch - a system that reads every source someone cares about each day (changelogs and release notes, communities, feeds, videos, papers), makes a quick decision…
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Categories
Creates a comprehensive, context-rich implementation plan through deep codebase analysis, a short clarifying interview, and external research. Piv Plan Implementation is an agent skill from coleam00/skills. Creates a comprehensive, context-rich implementation plan through deep codebase analysis, a short clarifying interview, and external research.
Piv Plan Implementation fits situations like: you have a ticket; feature and need a one-pass-ready plan before writing any code.
Run `npx skills add coleam00/skills --skill piv-plan-implementation -a claude-code`. Or copy the skill folder (.claude/skills/piv-plan-implementation in coleam00/skills) into .claude/skills/piv-plan-implementation in your project. Claude Code loads it when a task matches its description.
Run `npx skills add coleam00/skills --skill piv-plan-implementation -a codex`. Or copy the skill folder (.claude/skills/piv-plan-implementation in coleam00/skills) into .agents/skills/piv-plan-implementation in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add coleam00/skills --skill piv-plan-implementation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/piv-plan-implementation, .gemini/skills/piv-plan-implementation, .github/skills/piv-plan-implementation and .opencode/skills/piv-plan-implementation in your project.
Going by SKILL.md and its folder, Piv Plan Implementation needs the command-line tools its instructions call (gh).
SKILL.md contains no URLs. Its commands use gh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
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.
Piv Plan Implementation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.9k tokens (SKILL.md is roughly 20k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Piv Plan Implementation: Run Jira (DataDog/datadog-agent, 3.8k stars), PRP Implementation Planner (Wirasm/prp, 2.3k stars), PRP Plan (Wirasm/prp, 2.3k stars) and sfdx-hardis Architecture Guide (hardisgroupcom/sfdx-hardis, 401 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
coleam00 (a GitHub user) maintains it in coleam00/skills, which has 670 GitHub stars. The repository holds 34 skills in this directory. The repository was last updated on October 7, 2026.
Source: coleam00/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.