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Absolute Spec

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maddhruv
absolute-spec

Lightweight standalone design spec for AI coding agents: codebase scan → bounded clarify pass (3–5 questions, not a grill) → reviewed design doc written to docs/plans/ → independent scored review → stop. No task board, no build. Use when you want a spec to discuss, hand off, or review before committing to implementation. Chains into absolute-work when ready to build. Triggers on "absolute spec", "write a spec", "spec out this feature", "draft a design doc", "I want a spec to hand off / review, don't build it yet".

Overview

Publishermaddhruv
Repositoryabsolute
Skill nameabsolute-spec
Stars
223
Forks
30
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by maddhruv on GitHub. Read the source before you install it.

Installation

Install the Absolute Spec AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/maddhruv/absolute/tree/main/skills/absolute-spec
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/maddhruv/absolute.git /tmp/absolute
mkdir -p .claude/skills
cp -r /tmp/absolute/skills/absolute-spec .claude/skills/absolute-spec
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Absolute Spec in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Absolute Spec on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Absolute Spec is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Start your first response with the 📋 emoji.

Absolute Spec

Absolute Spec turns a fuzzy intent into a reviewed design-spec document — then stops. It is the planning artifact of work, lifted out of the full lifecycle: scan the codebase, ask only the questions the code can't answer, write the spec, run an independent scored review, and hand back a doc you can discuss, hand off, or feed into /absolute work to build.

It is deliberately lightweight. No relentless interview, no task board, no decompose, no execution. One deliverable: a spec good enough that an unfamiliar developer could build from it.


When to use this command

Use spec when:

  • You want a design spec to discuss, review, or hand off — not build right now.
  • You need to think a feature through on paper before committing to implementation.
  • A teammate or another agent will do the building from your spec.
  • You want a fast, reviewed design doc without the full phase-gated lifecycle.

Do NOT use spec when:

  • You want to design AND build in one flow → use /absolute work (spec is its Phase 2, followed by decompose + safe-wave execution).
  • You're documenting code that already exists / already shipped → use /absolute docs (reference/explanation docs, not a forward design).
  • The change is a one-line obvious fix needing no design.

The line vs work: spec produces a doc and stops; work produces a doc and then builds it. If you're unsure whether you'll build it now, start with spec — you can chain into work afterward and it will pick the spec up.


Key Principles

  1. Codebase before questions. Read what exists first; ask only what code can't answer.
  2. Bounded, not relentless. A short clarify pass (3–5 questions), not the depth-first grill work runs. Batching questions is fine.
  3. The spec is the deliverable. Quality matters more here than anywhere — keep the independent scored review.
  4. Reuse, don't reinvent. Template, scaling rules, and review rubric come from absolute-work's references/spec-writing.md. This command is the thin flow around them.
  5. Stop after review. No code, no board, no execution. Hand off cleanly.
  6. Never auto-commit. Write the spec file and report; the user commits.

The Flow

SCAN ─→ CLARIFY ─→ WRITE ─→ REVIEW ─→ HANDOFF

No hard gates between steps (that's work). The one checkpoint is the clarify pass — ask, get answers, then proceed straight through to a reviewed spec.


Step 1 — SCAN

Ground the spec in reality before asking anything.

  1. Convention detection — read cached config first: if .absolute.config.json or ~/.absolute/config.json exists (from /absolute init), resolve the effective config (project file → global projects["<cwd>"] → global defaults) and use its conventions, detecting only what's missing. No config → soft-suggest init and run work's Codebase Convention Detection table (package manager, language/runtime, test runner, linter, build system, directory conventions; see absolute-work's SKILL.md under Codebase Convention Detection). The spec must speak the project's real stack, scripts, and paths.
  2. Deep context scan — read what exists: docs/ (README first), root README.md, CLAUDE.md, CONTRIBUTING.md, docs/plans/ (overlapping/related designs), recent commits (last 10–20), package manifests, and the directories the feature touches.
  3. Synthesize — state what you learned in 2–4 lines (stack, relevant existing code, any overlapping prior design). Do not dump a file listing.

Detect the work type (feature / refactor / greenfield / migration) only enough to shape the spec — spec does not run the full per-type question banks.


Step 2 — CLARIFY (bounded pass)

Ask only the questions the codebase genuinely cannot answer — the preference and scope forks. Cap at 3–5 questions; batching is allowed (one AskUserQuestion call with multiple questions where available).

Good questions to ask (when code can't answer them):

  • Scope boundary — what's in v1 vs explicitly deferred.
  • Behavior forks — real-time vs batch, sync vs async, the genuine "which way" decisions.
  • Data/contract shape — only where the design hinges on it and code gives no signal.
  • Non-goals — what this explicitly will NOT do.

Do NOT ask: anything a config, manifest, test file, or existing pattern already states. When the code answers it, say so in the spec instead of asking.

If the user said "no questions, just draft it" — skip to WRITE and capture every guess in an ## Open Questions / assumptions section instead.


Step 3 — WRITE

Write the spec to <specDir>/YYYY-MM-DD-<topic>-design.md (<topic> = short kebab-case slug). <specDir> is preferences.specDir from config when present, else docs/plans.

Use the template, section-scaling rules, writing style, and Decision Log format from absolute-work's references/spec-writing.md — that file is the single source of truth; do not restate it here, load it. In particular:

  • Pick the complexity tier (Simple / Medium / Complex) using the complexity heuristic table, and scale sections accordingly. Remove sections that would only say "N/A".
  • Be concrete: real file paths, real endpoints, real schemas in code blocks — never "an endpoint for X".
  • Fill the Decision Log with the forks resolved in CLARIFY plus any you recommended, each with a one-line rationale.

Step 4 — REVIEW (scored, independent)

Dispatch a separate reviewer subagent — the agent that wrote the spec does not grade it (generator ≠ evaluator). Use the rubric and reviewer prompt template verbatim from absolute-work's references/spec-writing.md (Scored Spec Review Protocol): graded on Completeness, Consistency, Clarity, Scope, Testability (1–5 each, weighted).

Weighted ScoreVerdictAction
4.0 – 5.0ApprovedProceed to HANDOFF
3.0 – 3.9Needs WorkFix the flagged issues, re-dispatch (max 3 iterations)
< 3.0Major GapsSurface to the user immediately; do not silently iterate

Reviewer approval is necessary but not the end — the user still has the final say at HANDOFF.


Step 5 — HANDOFF

  1. Present — the spec path, the complexity tier, and the reviewer's weighted score + verdict. Summarize the key decisions in 2–4 lines.
  2. Offer to build — chain into /absolute work, which will pick up the spec at its decompose phase rather than re-running intake. Make this an explicit, optional next step.
  3. Stop. No code, no board. Never run git commit — suggest a message if asked; the user commits.

Gotchas

  1. Drifting into work. If you start decomposing into tasks or writing code, you've left spec. Stop at the reviewed doc.
  2. Asking what the code answers. The bounded pass is for preferences and forks only — scan first, ask second.
  3. Skipping the review to "stay light". The review is the cheap quality gate that makes a standalone spec trustworthy. Keep it.
  4. Restating spec-writing.md. Load it; don't copy the template/rubric in here — two copies drift.
  5. Over-asking. More than ~5 questions means you're running work's interview. Tighten.

Output / Response Style

Respond terse like smart caveman. All technical substance stay. Only fluff die. Drop articles, filler, pleasantries, hedging. Fragments OK. Technical terms exact. Code blocks and quoted errors unchanged. Drop caveman for security warnings, irreversible-action confirmations, and any multi-step sequence where fragment order risks misread; resume after. Spec prose itself is written normally (it's a deliverable, not chat).


Companion commands

Sibling commands in this skill chain naturally around spec:

  • /absolute work — build what the spec describes (picks the spec up at decompose).
  • /absolute ui — design the interface for a feature the spec defines.
  • /absolute docs — once it's built and shipped, document it for readers.

Suggest them where relevant; they're always available (same skill, no extra install).

Frequently asked questions

What does the Absolute Spec AI skill do?

Lightweight standalone design spec for AI coding agents: codebase scan → bounded clarify pass (3–5 questions, not a grill) → reviewed design doc written to docs/plans/ → independent scored review → stop. No task board, no build. Use when you want a spec to discuss, hand off, or review before committing to implementation. Chains into absolute-work when ready to build. Triggers on "absolute spec", "write a spec", "spec out this feature", "draft a design doc", "I want a spec to hand off / review, don't build it yet".

Why use Absolute Spec on TypingMind?

Because you install it once and use it with any model. Absolute Spec is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Absolute Spec in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/maddhruv/absolute/tree/main/skills/absolute-spec. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Absolute Spec?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Absolute Spec?

As many as you like. As long as a model supports skills, you can use Absolute Spec with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Absolute Spec AI skill free?

Yes. It is published on GitHub by maddhruv under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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