ATASTECH
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pitroom-writing-plans
Use when you have a spec or requirements for a multi-step task, before touching code - writes a task-by-task implementation plan that Pitroom workers can execute.
Overview
Use when you have a spec or requirements for a multi-step task, before touching code - writes a task-by-task implementation plan that Pitroom workers can execute.
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Writing Plans
Overview
Write comprehensive implementation plans assuming the engineer has zero context for our codebase and questionable taste. Document everything they need to know: which files to touch for each task, code, testing, docs they might need to check, how to test it. Give them the whole plan as bite-sized tasks. DRY. YAGNI. TDD. Frequent commits.
Assume they are a skilled developer, but know almost nothing about our toolset or problem domain. Assume they don't know good test design very well.
Announce at start: "I'm using the pitroom-writing-plans skill to create the implementation plan."
Context: If working in an isolated worktree, it should have been created via the pitroom-worktrees skill at execution time.
Save plans to: docs/pitroom/plans/YYYY-MM-DD-<feature-name>.md
- (User preferences for plan location override this default)
Scope Check
If the spec covers multiple independent subsystems, it should have been broken into sub-project specs during brainstorming. If it wasn't, suggest breaking this into separate plans — one per subsystem. Each plan should produce working, testable software on its own.
File Structure
Before defining tasks, map out which files will be created or modified and what each one is responsible for. This is where decomposition decisions get locked in.
- Design units with clear boundaries and well-defined interfaces. Each file should have one clear responsibility.
- You reason best about code you can hold in context at once, and your edits are more reliable when files are focused. Prefer smaller, focused files over large ones that do too much.
- Files that change together should live together. Split by responsibility, not by technical layer.
- In existing codebases, follow established patterns. If the codebase uses large files, don't unilaterally restructure - but if a file you're modifying has grown unwieldy, including a split in the plan is reasonable.
This structure informs the task decomposition. Each task should produce self-contained changes that make sense independently.
Task Right-Sizing
A task is the smallest unit that carries its own test cycle and is worth a fresh reviewer's gate. When drawing task boundaries: fold setup, configuration, scaffolding, and documentation steps into the task whose deliverable needs them; split only where a reviewer could meaningfully reject one task while approving its neighbor. Each task ends with an independently testable deliverable.
Worker Tier
Every task names the worker tier that implements it, on its own line right under the heading: **Worker:** cheap, **Worker:** standard or **Worker:** capable. pitroom run --plan uses it when the executor names no worker; the user's config maps tiers to workers (tiers).
- cheap: the task text contains the complete code (implementation is transcription plus testing), or a single-file mechanical fix.
- standard: several files with integration concerns, or an implementer working from prose.
- capable: design judgment or broad understanding of the codebase.
Turn count beats token price: the cheapest models take 2-3× the turns on multi-step work. The user prefers the free tier, so start with cheap for everything a cheap worker can plausibly do and raise only the tasks that need more; a failed cheap task costs one retry on a higher tier. When you are truly unsure between two tiers for a task that is costly to redo, take the higher.
Bite-Sized Task Granularity
Each step is one action (2-5 minutes):
- "Write the failing test" - step
- "Run it to make sure it fails" - step
- "Implement the minimal code to make the test pass" - step
- "Run the tests and make sure they pass" - step
- "Commit" - step
Plan Document Header
Every plan MUST start with this header:
# [Feature Name] Implementation Plan
> **For agentic workers:** REQUIRED SUB-SKILL: Use pitroom-driven-development to implement this plan task-by-task (each task runs as `pitroom run -i --plan <this file> --step N`). Steps use checkbox (`- [ ]`) syntax for tracking.
**Goal:** [One sentence describing what this builds]
**Architecture:** [2-3 sentences about approach]
**Tech Stack:** [Key technologies/libraries]
**Spec:** [path to the spec/design doc this plan implements — the plan
argues from the spec, so the spec travels with it; executors read both]
## Global Constraints
[The spec's project-wide requirements — version floors, dependency limits,
naming and copy rules, platform requirements — one line each, with exact
values copied verbatim from the spec. Every task's requirements implicitly
include this section.]
---
Task Structure
Task headings are exactly ### Task N: <name>: pitroom run --plan finds tasks by them, and a task runs until the next heading of the same or a higher level.
### Task N: [Component Name]
**Worker:** cheap | standard | capable
**Files:**
- Create: `exact/path/to/file.py`
- Modify: `exact/path/to/existing.py:123-145`
- Test: `tests/exact/path/to/test.py`
**Interfaces:**
- Consumes: [what this task uses from earlier tasks — exact signatures]
- Produces: [what later tasks rely on — exact function names, parameter
and return types. A task's implementer sees only their own task; this
block is how they learn the names and types neighboring tasks use.]
- [ ] **Step 1: Write the failing test**
```python
def test_specific_behavior():
result = function(input)
assert result == expected
```
- [ ] **Step 2: Run test to verify it fails**
Run: `pytest tests/path/test.py::test_name -v`
Expected: FAIL with "function not defined"
- [ ] **Step 3: Write minimal implementation**
```python
def function(input):
return expected
```
- [ ] **Step 4: Run test to verify it passes**
Run: `pytest tests/path/test.py::test_name -v`
Expected: PASS
- [ ] **Step 5: Commit**
```bash
git add tests/path/test.py src/path/file.py
git commit -m "feat: add specific feature"
```
Workers never commit: an implementer skips commit steps, and the primary commits after the task's review, when it applies the patch. Write the commit step anyway; it tells the primary what to commit and how to word it.
No Placeholders
Every step must contain the actual content an engineer needs. These are plan failures — never write them:
- "TBD", "TODO", "implement later", "fill in details"
- "Add appropriate error handling" / "add validation" / "handle edge cases"
- "Write tests for the above" (without actual test code)
- "Similar to Task N" (repeat the code — the engineer may be reading tasks out of order)
- Steps that describe what to do without showing how (code blocks required for code steps)
- References to types, functions, or methods not defined in any task
Self-Review
After writing the complete plan, look at the spec with fresh eyes and check the plan against it. This is a checklist you run yourself — not a subagent dispatch.
1. Spec coverage: Skim each section/requirement in the spec. Can you point to a task that implements it? List any gaps.
2. Placeholder scan: Search your plan for red flags — any of the patterns from the "No Placeholders" section above. Fix them.
3. Type consistency: Do the types, method signatures, and property names you used in later tasks match what you defined in earlier tasks? A function called clearLayers() in Task 3 but clearFullLayers() in Task 7 is a bug.
4. Headings and tiers: every task has a ### Task N: heading with a unique N and a **Worker:** line.
If you find issues, fix them inline. No need to re-review — just fix and move on. If you find a spec requirement with no task, add the task.
Execution Handoff
After saving the plan, optionally have a read-only worker check it with plan-document-reviewer-prompt.md (fill {{PLAN_FILE}} and {{SPEC_FILE}} with sed as in pitroom-brainstorming, run it with pitroom run --task-file). Then offer:
"Plan complete and saved to docs/pitroom/plans/<filename>.md. Two execution options:
1. Pitroom-driven (recommended) - a worker implements each task in an isolated copy, another model reviews it, I apply and commit between tasks
2. Inline - I execute the tasks myself in this session, with the same checkpoints
Which approach?"
Either way: REQUIRED SUB-SKILL: pitroom-driven-development (its "Inline execution" section covers option 2).
File metadata
name: pitroom-writing-plans description: Use when you have a spec or requirements for a multi-step task, before touching code - writes a task-by-task implementation plan that Pitroom workers can execute.
View original text
---
name: pitroom-writing-plans
description: Use when you have a spec or requirements for a multi-step task, before touching code - writes a task-by-task implementation plan that Pitroom workers can execute.
---
# Writing Plans
## Overview
Write comprehensive implementation plans assuming the engineer has zero context for our codebase and questionable taste. Document everything they need to know: which files to touch for each task, code, testing, docs they might need to check, how to test it. Give them the whole plan as bite-sized tasks. DRY. YAGNI. TDD. Frequent commits.
Assume they are a skilled developer, but know almost nothing about our toolset or problem domain. Assume they don't know good test design very well.
**Announce at start:** "I'm using the pitroom-writing-plans skill to create the implementation plan."
**Context:** If working in an isolated worktree, it should have been created via the `pitroom-worktrees` skill at execution time.
**Save plans to:** `docs/pitroom/plans/YYYY-MM-DD-<feature-name>.md`
- (User preferences for plan location override this default)
## Scope Check
If the spec covers multiple independent subsystems, it should have been broken into sub-project specs during brainstorming. If it wasn't, suggest breaking this into separate plans — one per subsystem. Each plan should produce working, testable software on its own.
## File Structure
Before defining tasks, map out which files will be created or modified and what each one is responsible for. This is where decomposition decisions get locked in.
- Design units with clear boundaries and well-defined interfaces. Each file should have one clear responsibility.
- You reason best about code you can hold in context at once, and your edits are more reliable when files are focused. Prefer smaller, focused files over large ones that do too much.
- Files that change together should live together. Split by responsibility, not by technical layer.
- In existing codebases, follow established patterns. If the codebase uses large files, don't unilaterally restructure - but if a file you're modifying has grown unwieldy, including a split in the plan is reasonable.
This structure informs the task decomposition. Each task should produce self-contained changes that make sense independently.
## Task Right-Sizing
A task is the smallest unit that carries its own test cycle and is worth a
fresh reviewer's gate. When drawing task boundaries: fold setup,
configuration, scaffolding, and documentation steps into the task whose
deliverable needs them; split only where a reviewer could meaningfully
reject one task while approving its neighbor. Each task ends with an
independently testable deliverable.
## Worker Tier
Every task names the worker tier that implements it, on its own line right under the heading: `**Worker:** cheap`, `**Worker:** standard` or `**Worker:** capable`. `pitroom run --plan` uses it when the executor names no worker; the user's config maps tiers to workers (`tiers`).
- **cheap**: the task text contains the complete code (implementation is transcription plus testing), or a single-file mechanical fix.
- **standard**: several files with integration concerns, or an implementer working from prose.
- **capable**: design judgment or broad understanding of the codebase.
Turn count beats token price: the cheapest models take 2-3× the turns on multi-step work. The user prefers the free tier, so start with `cheap` for everything a cheap worker can plausibly do and raise only the tasks that need more; a failed cheap task costs one retry on a higher tier. When you are truly unsure between two tiers for a task that is costly to redo, take the higher.
## Bite-Sized Task Granularity
**Each step is one action (2-5 minutes):**
- "Write the failing test" - step
- "Run it to make sure it fails" - step
- "Implement the minimal code to make the test pass" - step
- "Run the tests and make sure they pass" - step
- "Commit" - step
## Plan Document Header
**Every plan MUST start with this header:**
```markdown
# [Feature Name] Implementation Plan
> **For agentic workers:** REQUIRED SUB-SKILL: Use pitroom-driven-development to implement this plan task-by-task (each task runs as `pitroom run -i --plan <this file> --step N`). Steps use checkbox (`- [ ]`) syntax for tracking.
**Goal:** [One sentence describing what this builds]
**Architecture:** [2-3 sentences about approach]
**Tech Stack:** [Key technologies/libraries]
**Spec:** [path to the spec/design doc this plan implements — the plan
argues from the spec, so the spec travels with it; executors read both]
## Global Constraints
[The spec's project-wide requirements — version floors, dependency limits,
naming and copy rules, platform requirements — one line each, with exact
values copied verbatim from the spec. Every task's requirements implicitly
include this section.]
---
```
## Task Structure
Task headings are exactly `### Task N: <name>`: `pitroom run --plan` finds tasks by them, and a task runs until the next heading of the same or a higher level.
````markdown
### Task N: [Component Name]
**Worker:** cheap | standard | capable
**Files:**
- Create: `exact/path/to/file.py`
- Modify: `exact/path/to/existing.py:123-145`
- Test: `tests/exact/path/to/test.py`
**Interfaces:**
- Consumes: [what this task uses from earlier tasks — exact signatures]
- Produces: [what later tasks rely on — exact function names, parameter
and return types. A task's implementer sees only their own task; this
block is how they learn the names and types neighboring tasks use.]
- [ ] **Step 1: Write the failing test**
```python
def test_specific_behavior():
result = function(input)
assert result == expected
```
- [ ] **Step 2: Run test to verify it fails**
Run: `pytest tests/path/test.py::test_name -v`
Expected: FAIL with "function not defined"
- [ ] **Step 3: Write minimal implementation**
```python
def function(input):
return expected
```
- [ ] **Step 4: Run test to verify it passes**
Run: `pytest tests/path/test.py::test_name -v`
Expected: PASS
- [ ] **Step 5: Commit**
```bash
git add tests/path/test.py src/path/file.py
git commit -m "feat: add specific feature"
```
````
Workers never commit: an implementer skips commit steps, and the primary commits after the task's review, when it applies the patch. Write the commit step anyway; it tells the primary what to commit and how to word it.
## No Placeholders
Every step must contain the actual content an engineer needs. These are **plan failures** — never write them:
- "TBD", "TODO", "implement later", "fill in details"
- "Add appropriate error handling" / "add validation" / "handle edge cases"
- "Write tests for the above" (without actual test code)
- "Similar to Task N" (repeat the code — the engineer may be reading tasks out of order)
- Steps that describe what to do without showing how (code blocks required for code steps)
- References to types, functions, or methods not defined in any task
## Self-Review
After writing the complete plan, look at the spec with fresh eyes and check the plan against it. This is a checklist you run yourself — not a subagent dispatch.
**1. Spec coverage:** Skim each section/requirement in the spec. Can you point to a task that implements it? List any gaps.
**2. Placeholder scan:** Search your plan for red flags — any of the patterns from the "No Placeholders" section above. Fix them.
**3. Type consistency:** Do the types, method signatures, and property names you used in later tasks match what you defined in earlier tasks? A function called `clearLayers()` in Task 3 but `clearFullLayers()` in Task 7 is a bug.
**4. Headings and tiers:** every task has a `### Task N:` heading with a unique N and a `**Worker:**` line.
If you find issues, fix them inline. No need to re-review — just fix and move on. If you find a spec requirement with no task, add the task.
## Execution Handoff
After saving the plan, optionally have a read-only worker check it with [plan-document-reviewer-prompt.md](plan-document-reviewer-prompt.md) (fill `{{PLAN_FILE}}` and `{{SPEC_FILE}}` with `sed` as in `pitroom-brainstorming`, run it with `pitroom run --task-file`). Then offer:
**"Plan complete and saved to `docs/pitroom/plans/<filename>.md`. Two execution options:**
**1. Pitroom-driven (recommended)** - a worker implements each task in an isolated copy, another model reviews it, I apply and commit between tasks
**2. Inline** - I execute the tasks myself in this session, with the same checkpoints
**Which approach?"**
Either way: **REQUIRED SUB-SKILL:** `pitroom-driven-development` (its "Inline execution" section covers option 2).
Review the source
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Free to get does not mean free to run. Price labels are not safety ratings. Submit pricing information →
Skill source recorded
Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.
Review before install: Avoid automatic install
License: MIT
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Financial research output is not financial advice; require human review before any live investment decision
- Low GitHub adoption signal
- AI review approval is missing
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 23 GitHub stars
- Stars/forks activity: 23 stars, 2 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.
Start with one small task
- 1Read the source. Confirm the input, expected output, dependencies and permissions.
- 2Ask your agent for a plan. Approve setup and any costs before running a small isolated test.
- 3Check the output and changed files. Report only what actually ran; keep the source revision for reproduction.
Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.
Source & usage notes
IndexedStatic Checked
Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.
- Source repository
- ATASTECH/pitroom
- License
- MIT
- Version
- Unknown
- Last GitHub push
- Oct 3, 2026
- Registry updated
- Oct 3, 2026
- Instruction path
- skills/pitroom-writing-plans/SKILL.md @ dcbd4d9042c2
Version reported in registry metadata; check source releases before relying on it.
Quality
55/100
Promising
Trust
58/100
Do not auto-install
Audit
71/100
Needs review
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Financial research output is not financial advice; require human review before any live investment decision
- Low GitHub adoption signal
- AI review approval is missing
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 23 GitHub stars
- Stars/forks activity: 23 stars, 2 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Verified installs
- —
- Outcomes
- —
Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.
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This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
More details
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"Permission surface needs review: secrets or environment access, shell or command execution",
"GitHub adoption: 23 GitHub stars",
"Stars/forks activity: 23 stars, 2 forks; issue activity unavailable in current metadata",
"Dependency/runtime risk: command execution surface, credential or environment access"
]
},
"agent_proven": {
"version": "agent-proven-v1",
"score": 0,
"tier": "unproven",
"label": "Needs first agent run",
"summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
"metrics": {
"totalOutcomes": 0,
"successfulOutcomes": 0,
"failedOutcomes": 0,
"installAttempts": 0,
"installSuccessRate": null,
"successRate": null,
"recentSuccessRate": null,
"recentFailureRate": null,
"riskBlocked": 0,
"setupRequired": 0,
"notRelevant": 0,
"avgOutputQuality": null,
"avgTimeToUsefulMs": null,
"productionOutcomes": 0,
"humanReviewRequired": 0,
"uniqueAgents": 0,
"lastOutcomeAt": null
},
"signals": [],
"penalties": [
"No real agent outcome evidence yet"
]
},
"audit": {
"score": 71,
"risk_level": "needs_review",
"risk_label": "Needs review",
"warnings": [
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
"Financial research output is not financial advice; require human review before any live investment decision",
"Low GitHub adoption signal",
"AI review approval is missing",
"Financial research output is not financial advice; require human review before any live investment decision.",
"Quality score needs review",
"Permission surface needs review: secrets or environment access, shell or command execution"
]
},
"safety_gate": {
"tier": "blocked",
"label": "Blocked for auto-install",
"auto_install_policy": "block",
"auto_install_allowed": false,
"human_review_required": true,
"blocked": true,
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
},
"quality": {
"score": 55,
"label": "Promising"
},
"supply": {
"track": "Coding and developer agents",
"scenario": "Coding agents",
"maintenance": "Pushed today",
"risk": "Needs review"
},
"alternative_skills": [
{
"slug": "mattpocock-implement",
"name": "Implement",
"url": "https://www.openagentskill.com/skills/mattpocock-implement",
"stars": 175741,
"install_command": "",
"trust_score": 89,
"audit_score": 91
}
],
"do_not_use_when": [
"teams that need a vendor-supported SLA",
"production agents without a repository review",
"Low GitHub adoption signal",
"High-risk permission hints: Shell or command execution, Secrets or environment access",
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
"Financial research output is not financial advice; require human review before any live investment decision",
"AI review approval is missing"
],
"agent_contract": {
"task_input": "Use pitroom-writing-plans in an agent workflow",
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
"install_policy": "block",
"minimum_review_before_use": [
"Trust: 66/100 Manual review",
"Audit: 71/100 Needs review",
"Safety: 31/100 Avoid automatic install",
"Review repository, license, install command, and permission surface before production use."
],
"expected_agent_output": {
"selected_skill": "atastech-pitroom-writing-plans (pitroom-writing-plans)",
"install_command": "npx skills add ATASTECH/pitroom --skill pitroom-writing-plans",
"risk_summary": "Needs review; Blocked for auto-install; Review before production",
"verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
}
},
"outcome_feedback": {
"endpoint": "https://www.openagentskill.com/api/agent/outcome",
"method": "POST",
"requires_resolve_event_id": true,
"event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
"expected_outcomes": [
"success",
"failed",
"not_relevant",
"blocked_by_risk",
"setup_required"
],
"payload_template": {
"event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
"skill_slug": "atastech-pitroom-writing-plans",
"task": "Use pitroom-writing-plans in an agent workflow",
"agent": "codex",
"outcome": "success",
"install_used": true,
"risk_blocked": false,
"setup_required": false,
"task_success": true,
"output_quality": 4,
"error_type": null,
"human_review_required": false,
"workspace": "sandbox",
"time_to_useful_ms": 120000,
"notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
}
},
"endpoints": {
"web": "https://www.openagentskill.com/skills/atastech-pitroom-writing-plans",
"api": "https://www.openagentskill.com/api/agent/skills/atastech-pitroom-writing-plans",
"audit": "https://www.openagentskill.com/skills/atastech-pitroom-writing-plans/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=atastech-pitroom-writing-plans&task=Use%20pitroom-writing-plans%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20pitroom-writing-plans%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20pitroom-writing-plans%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/atastech-pitroom-writing-plans/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/atastech-pitroom-writing-plans"
}
}For the creator
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- Creator
- ATASTECH
- Source
- ATASTECH/pitroom
- Indexed by
- OpenAgentSkill community index
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