implementation-plan

implementation-plan is a skill for Claude Code, Codex from GreatMark/fable-field-guide-skills. It costs 164 tokens per session (1,578 once invoked), scanned A, original, MIT.

A guide for writing an implementation plan: a reviewable outline of decisions, affected code, and work needed before development starts.

In plain words
What is it for?
Use it when preparing an implementation plan, technical proposal, RFC, or development plan, and when reviewing the code and project information that the plan depends on.
Why use it?
It helps expose choices that may change early, before they become expensive to revise in code.

Skill for Claude CodeCodex

Part of the fable-field-guide-skills plugin — 9 skills, 2 hooks shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/greatmark/fable-field-guide-skills/implementation-plan
Any agent
npx skills add GreatMark/fable-field-guide-skills --skill implementation-plan
Clone the repo
git clone --depth 1 https://github.com/GreatMark/fable-field-guide-skills

Made for: Claude Code, Codex.

Or install fable-field-guide-skills, the plugin that ships this one along with the rest of its 9 skills, 2 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for implementation-plan

README.md
[![agentmods](https://agentmods.dev/badge/skills/greatmark/fable-field-guide-skills/implementation-plan.svg)](https://agentmods.dev/skills/greatmark/fable-field-guide-skills/implementation-plan)
Your own site
<a href="https://agentmods.dev/skills/greatmark/fable-field-guide-skills/implementation-plan"><img src="https://agentmods.dev/badge/skills/greatmark/fable-field-guide-skills/implementation-plan.svg" alt="Measured on agentmods" height="20"></a>
Per session 164 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,578 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00164 $0.01578
Opus 5 $0.00082 $0.00789
Sonnet 5 $0.00033 $0.00316
Haiku 4.5 $0.00016 $0.00158

Measured 5d ago against content hash 4e9ba9ac2774, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

implementation-plan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/implementation-plan/SKILL.md · 126 lines

How it starts

The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Implementation Plan

A plan's job is to surface the things the user might actually need to alter, before changing them becomes expensive. Order it by likelihood of change, not by execution order.

Workflow

  1. Check the escape hatch. If the change is single-file, touches no interface, data, or UX, and has only one sensible way to do it, say so in one sentence and start — no plan. If a reviewed plan for this task already exists, do not rewrite it: confirm it still stands, then start implementing with implementation-notes.
  2. Gather the inputs. Collect what this plan is based on: the brainstorm, spec, interview decisions (from earlier in the conversation, or from interview-decisions.md in the project root if the interview ran in a previous session), an existing implementation-plan.md when continuing earlier planning, the porting checklist from an earlier reference hunt (porting-checklist.md, if present), any chosen prototype under ./design-directions/, plus a read of the code that will be touched. If the chat contradicts interview-decisions.md, the latest chat statement wins — but promote the conflict to a pinned decision entry ("changed from X per your latest comment — confirm?"). If key inputs are missing: when the missing answers would overturn more than one top decision, run interview-me first; otherwise record explicit assumptions marked "(assumed — not confirmed)" and pin them at the top of the decision section regardless of sort order.
  3. Sort by likelihood of change, not chronology. Lead with the decisions the user is most likely to tweak — data model and schema changes, new type interfaces and API shapes, anything user-facing (examples; the authoritative sort key is in Rules). Bury the mechanical refactoring at the bottom — the user trusts the agent on that part.
  4. Make the top decisions reviewable. For each high-change-risk decision: the chosen option, 1-2 alternatives considered, and what changing it later would cost.
  5. Mark the improvisation zones. Flag the areas where unknowns are likely to surface mid-implementation, and state the fallback posture for each (e.g. "pick the conservative option and log it").
  6. End with an explicit go/no-go. Present the plan in chat — decision list first — and ask the user to approve, adjust, or reject. If review spans sessions or more than one round, persist the current draft as implementation-plan.md marked status: draft (apply the step 6 exclude when first writing it); flip it to approved on approval. On a vague pass ("looks fine, go ahead"), treat only the decisions actually discussed as approved: restate each undiscussed high-risk decision in one line, then persist.
  7. On approval, persist and hand off. Write the approved plan to implementation-plan.md in the project root (or flip the draft's status), in the language of the conversation, using the skeleton below. If the file already exists from a different task, never overwrite it silently: append a new plan section, or rename the old file to implementation-plan-<date>.md and say so. Do not commit it unless the user asks. If this is a git repo, exclude it locally: n=implementation-plan.md; p="$(git rev-parse --git-path info/exclude 2>/dev/null)" && { mkdir -p "$(dirname "$p")" && { grep -qxF "$n" "$p" || echo "$n" >> "$p"; }; } 2>/dev/null || echo "note: could not exclude $n — leaving it untracked, never staging it" Then suggest starting implementation in a fresh session with implementation-plan.md (and any prototypes) passed in as artifacts. Either way, once implementation kicks off — especially in a new session — keep notes per the implementation-notes skill, with implementation-plan.md as the Context input of implementation-notes.md.

Read the full file on GitHub · 126 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 126 lines · 164 tokens per session scan A 4e9ba9ac2774

Subscribe to this mod's changes

implementation-plan is a skill published in the GitHub repository GreatMark/fable-field-guide-skills (9 stars, last pushed 28d ago), licensed MIT. It adds 164 tokens to every session and 1,578 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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