Agent skill

Manual Planning

by fjrevoredo in fjrevoredo/mini-diarium

Create, update, review, and execute manual Markdown implementation plans when harness planning mode is not being used.

MITAuto-check passedAgent Workflows

Install Manual Planning

skills CLI
$ npx skills add fjrevoredo/mini-diarium --skill manual-planning -a claude-code

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

GitHub CLI
$ gh skill install fjrevoredo/mini-diarium manual-planning --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/fjrevoredo/mini-diarium.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/manual-planning .claude/skills/manual-planning && 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
manual-planning
GitHub stars
309
Token cost
~3.7k tokens
SKILL.md length
1,930 words
Files
10 (incl. scripts, references, assets)
Skills in repo
41
Repo updated
First seen
Licence
MIT

At a glance

Create, update, review, and execute manual Markdown implementation plans when harness planning mode is not being used.

  • Works in 6 steps: Gather enough repository context to… → Create the file with new-plan.py,… → Fill in the template. Every factual… → …
  • The user asks for a plan file
  • SKILL.md covers Scripts, Default Location, Plan Tracking and Plan Creation Workflow, plus 13 more sections
  • Runs Python scripts from its folder; calls python3, uv and git

What it does

Manual Planning is an agent skill from fjrevoredo/mini-diarium. Create, update, review, and execute manual Markdown implementation plans when harness planning mode is not being used. Use when the user asks for a plan file, manual plan, implementation plan, execution plan, roadmap, task checklist, planning document, or agent-maintained plan with statuses, validations, milestones, approval gates, and cleanup steps. Also use when resuming or maintaining an existing plan — marking a task complete, checking plan status, recording a decision, or validating a plan file — even when…

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files, including scripts, reference files and assets (for example `agents/openai.yaml`, `assets/milestoned-plan-template.md` and `assets/simple-plan-template.md`).

It sits in Agent Workflows, covering Planning, Project management and Architecture decision records. The repository describes itself as: A local-only journal with serious encryption. Free, open source, and never touches the internet. The licence is MIT.

When your agent uses it

  • The user asks for a plan file
  • Implementation plan
  • Planning document
  • Agent-maintained plan with statuses

Example prompts

  • “plan file”
  • “/manual-planning”

Requirements

  • Python 3

Workflow steps

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

  1. Gather enough repository context to identify scope, dependencies, test surfaces, and likely
  2. Create the file with new-plan.py, choosing --milestoned for more than 10 tasks.
  3. Fill in the template. Every factual claim carries evidence: a file:line reference, a section
  4. Set Plan Status to QUESTIONS PENDING if clarification is required, then surface the
  5. Incorporate the answers, run check-plan.py, and paste its output into ## Plan Self-Check.
  6. Set Plan Status to READY FOR APPROVAL only when the checker is clean and the only remaining

What it can do on your machine

Read from SKILL.md and the folder at commit 4627248. 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
    • uv
    • git

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

  • Network

    No URLs in SKILL.md. Its commands use uv and 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

Manual Planning loads about 3.7k tokens when it runs, and up to ~6.2k if it reads all its reference files. Until then it costs about 213 tokens; SKILL.md has 1,930 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~213
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.2k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from fjrevoredo/mini-diarium at commit 4627248, republished under its MIT licence (© fjrevoredo). 1,930 words, ~3,693 tokens.

Download SKILL.mdSave it as .claude/skills/manual-planning/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
manual-planning
description
Create, update, review, and execute manual Markdown implementation plans when harness planning mode is not being used. Use when the user asks for a plan file, manual plan, implementation plan, execution plan, roadmap, task checklist, planning document, or agent-maintained plan with statuses, validations, milestones, approval gates, and cleanup steps. Also use when resuming or maintaining an existing plan — marking a task complete, checking plan status, recording a decision, or validating a plan file — even when the user does not say "plan file". Triggers: plan file, manual plan, implementation plan, execution plan, planning document, plan template, resume plan, update the plan, continue the plan, plan status, task checklist, roadmap, milestones, exit criteria, approval gate, decision log, cleanup phase, check-plan, new-plan.
metadata.version
2.0.0

Manual Planning

Produce Markdown plans that another coding agent can execute without reinterpreting the original conversation. A plan is an execution ledger, not a proposal: it has to stay accurate while it is being worked through, and it has to be readable cold by a session that was not there when it was written.

Anything that can be checked mechanically is checked by a script. Do not hand-verify what check-plan.py verifies.

Scripts

Standard library Python 3 only — no install step. Run with python3 or uv run.

bash
# Create a plan: correct name, correct directory, version stamped from this SKILL.md
python3 scripts/new-plan.py "<title>" [--milestoned] [--dir docs/plans]
                                      [--exclude-locally | --tracked] [--force]

# Validate a plan (read-only). exit 0 = clean, 1 = errors, 2 = warnings only
python3 scripts/check-plan.py <plan-file> [--json] [--strict] [--dir docs/plans]

# Change one task's status, or read every status back
python3 scripts/plan-status.py <plan-file> set <task-id> "<STATUS>"
python3 scripts/plan-status.py <plan-file> show

Each answers --help, which lists every check ID and exit code. Quote the status argument: three of the five task statuses contain a space.

Default Location

docs/plans/YYYY-MM-DD-<name>-plan.md.

The date in the filename is the date of record, which is why the metadata block carries no Created or Last Updated field. new-plan.py produces both the directory and the filename, so neither is a rule you have to remember. Avoid names like notes.md, scratch.md or todo.md.

Plan Tracking

Default to not committing the plan. Follow the repo instead when it already has a convention: if the plan directory holds tracked plans, this project commits them. Commit the plan when the user asks.

If the plan stays untracked and its ?? entry interferes — a plan's own cleanup task validates with git status --porcelain — add the plan directory to .git/info/exclude rather than .gitignore; .gitignore is itself a tracked file, so editing it creates the commit you were avoiding. new-plan.py --exclude-locally does this and stamps Tracking: untracked (locally excluded).

Plan Creation Workflow

  1. Gather enough repository context to identify scope, dependencies, test surfaces, and likely risks. Everything you learn here goes in ## Context For A Clean Session — see references/context-and-evidence.md.
  2. Create the file with new-plan.py, choosing --milestoned for more than 10 tasks.
  3. Fill in the template. Every factual claim carries evidence: a file:line reference, a section reference (SKILL_RULES.md §5), or a re-runnable command.
  4. Set Plan Status to QUESTIONS PENDING if clarification is required, then surface the questions to the user. Mirror them in Open Questions.
  5. Incorporate the answers, run check-plan.py, and paste its output into ## Plan Self-Check.
  6. Set Plan Status to READY FOR APPROVAL only when the checker is clean and the only remaining gate is user approval.

Do not begin implementation until the user approves the plan, unless the user explicitly asks to proceed without approval. When approval is given, replace the ## Approval Gate boilerplate with Approved by <who> on <date>. — the section is a record, not a standing instruction.

Open Question Handling

Open questions are not plan-only notes. When clarification is needed, actively ask the user before marking the plan READY FOR APPROVAL.

  1. Use the native question-asking tool (question, ask-user, request-input, or whatever the current harness exposes). Always prefer a structured tool over plain text.
  2. If no such tool is available, send a concise formatted message in the conversation.
  3. Record both the question and the user's answer in Open Questions.
  4. After the user answers, replace the entry with the resolved answer, or the section with None.

Ask only questions that affect correctness, scope, risk, validation, sequencing, or approval. Do not ask what the repository can answer or what can safely become a stated assumption.

All open questions must be answered before the plan can transition to READY FOR APPROVAL.

Do not combine unresolved clarifying questions and final approval in the same user prompt.

Plan State Lifecycle

Plan Status in the metadata block is the authoritative plan-level state. It is modelled once — there is no separate Approval field, because in the surveyed corpus the two contradicted each other in 11 of 32 plans.

  1. DRAFT while creating the first version.
  2. QUESTIONS PENDING while waiting for required clarification.
  3. READY FOR APPROVAL after clarification is incorporated and the checker is clean.
  4. APPROVED after the user approves execution.
  5. IN PROGRESS while implementation is underway.
  6. COMPLETED after cleanup, ## Pre-flight Checks and final verification all pass.

Use BLOCKED when planning or implementation cannot continue, and record the blocker.

Plan Format Rules

Every plan has these top-level sections, which is what check-plan.py E009 enforces:

Metadata, Status Legend, Context For A Clean Session, Goal, Scope, Non-Goals, Assumptions, Open Questions, Milestones (or Tasks in a simple plan), Project Gates, Pre-flight Checks, Decision Log, Final Verification, Approval Gate, Plan Self-Check, Execution Notes.

The metadata block is exactly four fields:

markdown
- Plan Status: DRAFT
- Plan Format: manual-planning v2.0.0
- Template: milestoned
- Tracking: untracked

Use exactly these task statuses: TO BE DONE, IN PROGRESS, COMPLETED, BLOCKED, SKIPPED.

Use exactly these plan statuses: DRAFT, QUESTIONS PENDING, READY FOR APPROVAL, APPROVED, IN PROGRESS, COMPLETED, BLOCKED.

A status may carry a trailing annotation (COMPLETED — 381/381 passing); the vocabulary applies to the leading token.

More than 10 tasks requires milestones. With 10 or fewer, omit milestones unless they clarify independent delivery phases.

## Project Gates is where project-specific rules live — per-project lint/build/test commands, manual-verification requirements, changelog or backlog bookkeeping. Put them there rather than forking this skill for a project.

## Pre-flight Checks is a named checklist of the project's actual commands, run before the plan may reach COMPLETED. It is distinct from per-task validation: per-task validation proves one task worked, pre-flight checks prove the repository is shippable.

Task Rules

Each task must include:

  • Status: one of the task statuses.
  • Depends On: none, or a list of task numbers.
  • Objective: the observable outcome.
  • Steps: concrete implementation steps.
  • Validation: commands, tests, inspections, or self-checks that prove completion.
  • Notes: constraints, affected files, or None.

Task numbering is not an execution order. Depends On is the order. Task 3.1 may be runnable before Task 2.2.

Prefer deterministic validation — a test, build, linter, or exact file inspection. Where none is possible, state the manual check in observable terms. Say explicitly when a validation passes by producing no output: grep finding nothing exits 1, and so does diff on files that are meant to differ. An executing agent that branches on $? will read those as failures.

Milestone Rules

Each milestone must include Status, Purpose, Exit Criteria, and its tasks. Exit criteria must be broader than any single task validation: they confirm the completed tasks work together and that the next milestone can safely start.

Implementation Workflow

  1. Set the plan status to IN PROGRESS before starting implementation.
  2. Before starting a task, set it to IN PROGRESS — plan-status.py <plan> set <id> "IN PROGRESS".
  3. Complete the task.
  4. Run the task validation. Before declaring it passed, check the task's Steps and Validation for explicitly named tests (e.g. "add a test test_foo_bar"). A green test suite does not mean those tests were written — verify by name.
  5. Fix issues until validation passes, or mark the task BLOCKED with a reason.
  6. Set the task to COMPLETED immediately after validation passes.
  7. Update the milestone status when its tasks satisfy its exit criteria.
  8. Start the next task only after the plan file reflects the current state.

If validation was intentionally deferred earlier, reconcile the plan text once the deferred checks actually run. Leave no stale "validation pending" phrasing describing a state the plan has moved past.

Discovered issues. If a bug or unplanned problem is identified while working on a task, choose one path immediately — do not defer via a mental note:

  • Fix it in the current task if it is small and in scope.
  • Create a new task in the plan with status BLOCKED if it is out of scope for the current task.

A bug that is noticed but neither fixed nor recorded will be forgotten. There is no third option.

Show full SKILL.md (689 more words)Show less

Decision Log

## Decision Log is always present, in simple and milestoned plans alike. Deviations, discovered issues and deferred validations are the same shape of event and all land in this one append-only section.

Write an entry before moving to the next task, never retrospectively. Entries written after the fact are unreliable.

An entry is required when implementation diverges from what the plan specifies (different path, signature, or approach), when a validation failure forces the plan to adapt, when an unplanned problem is found, or when a validation is deliberately deferred. No entry is needed when execution matches the plan, or for wording differences that change no outcome.

markdown
### DEC-001 — <short title>

- Date: YYYY-MM-DD
- Task: <task number>
- Decision: <what was chosen>
- Rationale: <why>

Read references/decision-log.md when the inline log passes ~10 entries (check-plan.py warns with W005), when the user asks for a companion decisions file, or when you are unsure whether something qualifies as an entry.

Cleanup Phase

Every plan must include a cleanup task near the end, removing intermediate artifacts that should not ship: temporary documentation, one-off test cases, scratch scripts, temporary fixtures, generated data, debug logs, local-only outputs, and obsolete plan fragments.

Do not remove artifacts the user asked to keep, artifacts required for future maintainability, or generated files that are part of the repository contract.

Changelog steps are conditional. Add one only when the project actually has a changelog file. check-plan.py E010 looks for CHANGELOG* at the repository root and requires a task step mentioning it only when one exists — a project without a changelog needs no changelog step.

Plan Retirement

Untracked plans need no retirement step; deleting the file is enough.

Where plans are committed, the project owns the retirement convention, and check-plan.py must pass before a plan is retired: in a tracked repo a misleading final state is permanent.

Self-Check Before Approval

Run the checker and paste its output into ## Plan Self-Check with the date:

bash
python3 scripts/check-plan.py docs/plans/<plan>.md

Fix every error before requesting approval. Judge each warning on its merits and say in the plan why any surviving warning is acceptable.

Do not replace this with a hand-ticked list. The v1 hand-ticked self-check passed in 32 of 32 surveyed plans and failed in none — including on a plan with no Open Questions section that still claimed its open questions were explicit. It was a signature, not a gate.

Gotchas

  • A deployed skill copy can be older than its repository. Editing a repo changes nothing about what runs if the deployed path is a copy rather than a symlink into it. Check what the path actually resolves to (readlink, then read the file that comes back) before assuming an edit took effect.
  • Task numbering is not an execution order. That is what Depends On is for. Reading the numbers as a sequence serialises work that was designed to run in any dependency-respecting order.
  • .gitignore versus .git/info/exclude. .gitignore is tracked, so excluding an untracked plan there produces the very commit the untracked default avoids. Use .git/info/exclude.
  • A plan that reaches COMPLETED with tasks still TO BE DONE is the single most common way a plan ends up lying. Three surveyed plans were closed with every one of their 18–26 tasks still TO BE DONE. E005 catches it; plan-status.py warns as soon as a write creates it.
  • Statuses are scattered. A 26-task plan has 27+ status lines. Use plan-status.py set, which rewrites exactly one line, rather than editing by hand and missing some.
  • A validation that passes by producing no output exits non-zero. Read what the validation asserts rather than branching on $?.
  • Greenfield plans cannot cite line numbers in files that do not exist yet. That is why the evidence check only hardens (E011) when the plan names files that already exist, and otherwise only warns (W003).

References

  • references/context-and-evidence.md — read before writing ## Context For A Clean Session, or when a plan is being written for a session that will not have the originating conversation.
  • references/decision-log.md — read when the inline decision log passes ~10 entries, when a companion decisions file is requested, or when deciding whether an event qualifies as an entry.

Resources

new-plan.py copies the right one; copy by hand only if the script cannot run.

  • assets/simple-plan-template.md — 10 or fewer tasks.
  • assets/milestoned-plan-template.md — more than 10 tasks.

© fjrevoredo, 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 9 other files (scripts, references, assets) in .agents/skills/manual-planning of fjrevoredo/mini-diarium.

  • SKILL.md
  • agents/openai.yaml
  • assets/milestoned-plan-template.md
  • assets/simple-plan-template.md
  • evals/evals.json
  • references/context-and-evidence.md
  • references/decision-log.md
  • scripts/check-plan.py
  • scripts/new-plan.py
  • scripts/plan-status.py

Open the folder on GitHubat commit 4627248

Compare with similar skills

Manual Planning 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.

Manual Planning compared with similar skills
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Manual Planning this skillfjrevoredo/mini-diarium309—~3.7kAutomated safety check: PassMIT
Plan Previewu-ichi/reviewable-html-workbench2981 repos~1.8kAutomated safety check: PassMIT
Init My ProjectMCSLTeam/MCServerLauncher-Future121—~2.1kAutomated safety check: PassGPL-3.0
Idea To Implementation DocAkoliteZA/hermes-agent-idea-workflow272—~3.1kAutomated safety check: PassMIT
Planning With Filesguanyang/open-agent-hub9772 repos~9.7kAutomated safety check: NotesMIT
Designsynnaxlabs/synnax128—~4.5kAutomated safety check: PassCustom licence

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Categories

Questions about Manual Planning

What does Manual Planning do?

Create, update, review, and execute manual Markdown implementation plans when harness planning mode is not being used. Manual Planning is an agent skill from fjrevoredo/mini-diarium. Create, update, review, and execute manual Markdown implementation plans when harness planning mode is not being used.

When should I use Manual Planning?

Manual Planning fits situations like: the user asks for a plan file; implementation plan; planning document; agent-maintained plan with statuses.

How do I install Manual Planning in Claude Code?

Run `npx skills add fjrevoredo/mini-diarium --skill manual-planning -a claude-code`. Or copy the skill folder (.agents/skills/manual-planning in fjrevoredo/mini-diarium) into .claude/skills/manual-planning in your project. Claude Code loads it when a task matches its description.

How do I install Manual Planning in Codex?

Run `npx skills add fjrevoredo/mini-diarium --skill manual-planning -a codex`. Or copy the skill folder (.agents/skills/manual-planning in fjrevoredo/mini-diarium) into .agents/skills/manual-planning in your project. Codex loads it when a task matches its description.

Can I use Manual Planning 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 fjrevoredo/mini-diarium --skill manual-planning -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/manual-planning, .gemini/skills/manual-planning, .github/skills/manual-planning and .opencode/skills/manual-planning in your project.

What does Manual Planning need to run?

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

Does Manual Planning access the network?

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

Is Manual Planning 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 Manual Planning use?

Manual Planning 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 Manual Planning use?

About 3.7k tokens (SKILL.md is roughly 15k 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 2.5k tokens, read only when the agent opens those files.

What are the alternatives to Manual Planning?

Skills that share tags, products or a category with Manual Planning: Plan Preview (u-ichi/reviewable-html-workbench, 298 stars), Init My Project (MCSLTeam/MCServerLauncher-Future, 121 stars), Idea To Implementation Doc (AkoliteZA/hermes-agent-idea-workflow, 272 stars) and Planning With Files (guanyang/open-agent-hub, 977 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Manual Planning?

fjrevoredo (a GitHub user) maintains it in fjrevoredo/mini-diarium, which has 309 GitHub stars. The repository holds 41 skills in this directory. The repository was last updated on October 9, 2026.

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