Agent skill

Decide

by Abilityai in Abilityai/cornelius

Structure a decision, not just advise on it. An agent skill from Abilityai/cornelius.

MITAuto-check: notesProduct & Project Management

Install Decide

skills CLI
$ npx skills add Abilityai/cornelius --skill decide -a claude-code

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

GitHub CLI
$ gh skill install Abilityai/cornelius decide --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/Abilityai/cornelius.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/decide .claude/skills/decide && 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
decide
GitHub stars
109
Token cost
~2.7k tokens
SKILL.md length
939 words
Files
1
Skills in repo
54
Repo updated
First seen
Licence
MIT

At a glance

Structure a decision, not just advise on it. An agent skill from Abilityai/cornelius.

  • Works in 8 steps: Decision Guard (route before structuring) → Frame the Decision → Parallel Retrieval (one batch) → …
  • Stakes are on the table (X
  • SKILL.md covers Purpose, Problem, State Dependencies and Composes, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Decide is an agent skill from Abilityai/cornelius. Structure a decision, not just advise on it. Switches modes when the question is "what should we do" - expands the real option set (status quo, defer, pilot, hybrids), classifies the decision type (reversibility, one-shot vs repeated, ruin exposure, risk vs radical uncertainty), applies the MATCHING decision rule (ergodic filter, expected-value decomposition, robustness / minimax regret, value-of-information), and delivers a recommendation with tripwires. KB-grounded in the user's own decision-science frameworks…

Its SKILL.md is about 2.7k 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 Product & Project Management, covering Feature launches and release readiness. It works with MiniMax. The repository describes itself as: AI-powered second brain template for Claude Code + Obsidian. The licence is MIT.

When your agent uses it

  • Stakes are on the table (X
  • Go/no-go) - not for open exploration (/advise
  • /think-about-it) and never to relitigate a decision canon has already made (/canon-advise)

Example prompts

  • “what should we do”
  • “X or Y?”
  • “is it worth”
  • “/decide”

Requirements

  • Pre-approved tools (allowed-tools): Bash, Read, Grep, Glob

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Decision Guard (route before structuring)
  2. Frame the Decision
  3. Parallel Retrieval (one batch)
  4. Expand the Option Set
  5. Classify the Decision (this selects the machinery)
  6. Consequence Table + the Matching Rule
  7. Reasoning Checks (required - full battery)
  8. Decision Brief (output)

What it can do on your machine

Read from SKILL.md and the folder at commit b9bea90. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash
    • Read
    • Grep
    • Glob

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash and markdown).

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

  • Network

    No URLs in SKILL.md.

    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

Decide loads about 2.7k tokens when it runs. Until then it costs about 194 tokens; SKILL.md has 939 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~194
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash, Read, Grep, Glob

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.

SKILL.md

The full file from Abilityai/cornelius at commit b9bea90, republished under its MIT licence (© Abilityai). 939 words, ~2,661 tokens.

Download SKILL.mdSave it as .claude/skills/decide/SKILL.md (or your agent's skills folder).
name
decide
description
Structure a decision, not just advise on it. Switches modes when the question is "what should we do" - expands the real option set (status quo, defer, pilot, hybrids), classifies the decision type (reversibility, one-shot vs repeated, ruin exposure, risk vs radical uncertainty), applies the MATCHING decision rule (ergodic filter, expected-value decomposition, robustness / minimax regret, value-of-information), and delivers a recommendation with tripwires. KB-grounded in the user's own decision-science frameworks; runs the full reasoning-checks battery. Use when options or stakes are on the table ("X or Y?", "is it worth", go/no-go) - not for open exploration (/advise, /think-about-it) and never to relitigate a decision canon has already made (/canon-advise).
allowed-tools
Bash, Read, Grep, Glob
automation
autonomous
user-invocable
true
argument-hint
<the decision - options, stakes, constraints in natural language>
when_to_use
The question presents a choice between courses of action with real stakes - "should we do X or Y", "go/no-go on Z", "is it worth doing W now". Prefer /advise…
metadata.version
1.0
metadata.created
2026-07-31
metadata.updated
2026-07-31
metadata.author
Ability.ai
metadata.changelog
1.0: Initial version - standalone decision-theoretic sibling of /advise (per the 2026-07-31 self-audit + cross-model consensus: a separate skill, never an…

Decide

ℹ️ First, set expectations: print one line with this skill's version and its most recent change - the top of metadata.changelog - e.g. decide v1.0 — recent: initial decision-structuring skill. Then proceed.

Purpose

/advise produces a better map; /decide produces a choice. When the question is "what should we do", frameworks alone under-deliver - the output must be a recommendation produced by an explicit decision rule, with the losing options accounted for and tripwires attached. The KB skeleton is decision science (Kahneman / Gilbert / Tetlock / Thaler / Kay-King, bound by Ergodicity); this skill is where that skeleton actually decides instead of only describing.

Problem

$ARGUMENTS

State Dependencies

SourceLocationReadWrite
LBS searchresources/local-brain-search/run_search.sh✓
Core hubs (attractor check)resources/local-brain-search/run_connections.sh --hubs --json✓
KB notesBrain/**/*.md✓
Reasoning-checks contract.claude/skills/reasoning-checks/SKILL.md✓
Canon (conditional)Brain/Canon/**/*.md via canon-mounted search✓

Never writes. A decision brief may be saved to Brain/05-Meta/Reports/ only on explicit request (Step 8).

Composes

  • reasoning-checks - the shared discipline contract (applied per its applicability matrix, this skill runs the full battery)

Process

Step 1: Decision Guard (route before structuring)

Confirm this is actually a decision: two or more real courses of action, stakes, and someone who must choose. If it is understanding-seeking ("help me think about X") → /advise or /think-about-it. If it is a company-direction question canon already covers → /canon-advise governs; never relitigate a decided direction - /decide may still structure a new decision that canon leaves open (run one canon-mounted search BRAIN_READ_SCOPE=core,Canon when the subject smells like company direction; if a decision/spec note decides it, say so and stop).

Step 2: Frame the Decision

One block, before any retrieval:

  • Decision statement - the choice in one sentence
  • Decider + deadline - who chooses, by when, and what forces the timing (a decision with no deadline may be a defer candidate by default)
  • Irreversibility horizon - what becomes hard to undo, and when
Step 3: Parallel Retrieval (one batch)

Same fast-path discipline as /advise - no subagents, static search, one parallel batch. Read role: reasoning (contract: scope-mount): two passes per term, core as the spine and the reasoning mount as the evidence layer; run the scope-mount trigger check first and append ,company / ,thinkers / ,Books/<slug> to the wide pass on a hit.

bash
BRAIN_READ_SCOPE=core                          resources/local-brain-search/run_search.sh "[domain term 1]" --limit 3 --json
BRAIN_READ_SCOPE=core,Books,document-insights  resources/local-brain-search/run_search.sh "[domain term 1]" --limit 5 --json
BRAIN_READ_SCOPE=core                          resources/local-brain-search/run_search.sh "[domain term 2]" --limit 3 --json
BRAIN_READ_SCOPE=core,Books,document-insights  resources/local-brain-search/run_search.sh "[domain term 2]" --limit 5 --json
BRAIN_READ_SCOPE=core                          resources/local-brain-search/run_search.sh "[decision-structure term: ergodicity / optionality / reversibility / regret / explore exploit - match to the decision's shape]" --limit 3 --json
BRAIN_READ_SCOPE=core,Books,document-insights  resources/local-brain-search/run_search.sh "[the same decision-structure term]" --limit 5 --json
resources/local-brain-search/run_connections.sh --hubs --json   # fingerprint - always core; for the attractor check

Then read the 2-4 most relevant notes in parallel (frontmatter provenance: rides along for the checks).

Step 4: Expand the Option Set

The stated options are almost never the full set. Always add and assess:

  • Status quo - explicitly, with its own costs (doing nothing is a choice)
  • Defer - wait for information; a real option with a price (cost of delay) and a payoff (uncertainty resolved)
  • Pilot / staged commitment - buy information while moving
  • Hybrids - combinations the framing hid

Mark which options preserve optionality and which foreclose it.

Step 5: Classify the Decision (this selects the machinery)
AxisQuestionConsequence
ReversibilityTwo-way or one-way door?One-way → more analysis, prefer option-preserving moves
FrequencyOne-shot or repeated?Repeated → play expected value; one-shot → tails dominate
Ruin exposureDoes any option carry an absorbing barrier (can't come back from the bad tail)?Ergodic filter applies BEFORE any EV math
Uncertainty regimeAre probabilities honestly estimable (risk), or is this radical uncertainty?Radical uncertainty → robustness/regret, NOT invented probabilities
Show full SKILL.md (423 more words)Show less
Step 6: Consequence Table + the Matching Rule

Build a compact table: options × the 2-4 uncertainties that actually drive the outcome. Probabilities only where estimable and reference-class anchored (Check 4); payoffs in natural units, not scores.

Then apply the rule the classification selected - in this order:

  1. Ergodic filter first - eliminate any option with ruin exposure regardless of its EV ("EV-positive but you can't survive the bad branch" is a losing bet by the user's own core framework). Name what it eliminated.
  2. Risk + repeated/reversible → expected-value decomposition - show the components, not just the total.
  3. Radical uncertainty → robustness + minimax regret - which option is acceptable across all live scenarios; which minimizes the worst regret. Do NOT fake point probabilities to force an EV number - saying "this is not probabilizable" is the Kay-King discipline, not a cop-out.
  4. Value of information - if defer/pilot resolves a driving uncertainty and the delay cost is tolerable, the real option can beat both stated options.
  5. Regret cross-check - long-lens (would the 10-year view flip this?). A cross-check, never the primary rule.
Step 7: Reasoning Checks (required - full battery)

Apply .claude/skills/reasoning-checks/SKILL.md:

  • Epistemic Inversion on the recommendation - the pre-mortem is made for decisions; specific falsifier required
  • Reference Class - required in practice (a decision embeds forecasts; anchor every estimated probability/magnitude)
  • Attractor Check - against the hubs fetched in Step 3. Scope nuance: the check applies to the situation framing/diagnosis, not to the decision machinery itself - decision-science hubs (Decision Making, Ergodicity, Superforecasting) are this skill's tools by construction and do not count as attractor pull. What counts: the diagnosis leaning on 2+ top hubs.
  • Provenance Base - from the notes read in Step 3
Step 8: Decision Brief (output)
markdown
## Decision: [one-line statement]

**Type:** [reversible? one-shot/repeated? ruin exposure? risk/radical uncertainty] → **Rule applied:** [ergodic filter → EV | robustness/minimax regret | value-of-information]

**Option set considered:** [stated + added options; which were eliminated and by what]

**Consequence table:** [options × driving uncertainties]

**Recommendation:** [the choice, produced by the named rule - and why the losing options lose]

**Tripwires (revisit if):**
- [observable condition → what it changes]
- [date-based checkpoint if the decision was defer/pilot]

**KB grounding:** [[Note 1]], [[Note 2]] - [how each shaped the structure]

[reasoning-checks blocks: Epistemic Inversion · Reference Class · Attractor Check · Provenance Base]

On explicit request only: save the brief to Brain/05-Meta/Reports/decision-[slug]-YYYY-MM-DD.md (provenance: ai-inferred, standard frontmatter) - decision briefs are terminal deliverables, exactly what Reports/ is for. Never auto-save.

Rules

  • NO subagent spawning - fast path, all inline
  • Parallel batches - searches + hubs in one round, reads in one round; checks reuse those results
  • The recommendation must name its rule - "this is an EV call" vs "this is a robustness call" is the whole point of the mode-switch; a recommendation with no named rule is /advise output wearing a costume
  • Never fake probabilities under radical uncertainty - the regime classification is honest or the machinery is theater
  • Ruin trumps EV - the ergodic filter is not optional when an absorbing barrier is live
  • Tripwires always - a decision brief without revisit conditions is a prediction, not a decision
  • If the KB lacks relevant frameworks, say so and structure the decision from general principles, labelled as such

© Abilityai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/decide of Abilityai/cornelius.

Open the folder on GitHubat commit b9bea90

Compare with similar skills

Decide 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.

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Final Release Reviewopenai/openai-agents-python30k—~5.4kAutomated safety check: PassMIT
Final Release Reviewopenai/openai-agents-js3.9k—~4kAutomated safety check: PassMIT
Acceptance Demo GeneratorChachamaru127/claude-code-harness3.2k—~3.4kAutomated safety check: NotesMIT

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Works with

Questions about Decide

What does Decide do?

Structure a decision, not just advise on it. An agent skill from Abilityai/cornelius. Decide is an agent skill from Abilityai/cornelius. Structure a decision, not just advise on it.

When should I use Decide?

Decide fits situations like: stakes are on the table (X; go/no-go) - not for open exploration (/advise; /think-about-it) and never to relitigate a decision canon has already made (/canon-advise).

How do I install Decide in Claude Code?

Run `npx skills add Abilityai/cornelius --skill decide -a claude-code`. Or copy the skill folder (.claude/skills/decide in Abilityai/cornelius) into .claude/skills/decide in your project. Claude Code loads it when a task matches its description.

How do I install Decide in Codex?

Run `npx skills add Abilityai/cornelius --skill decide -a codex`. Or copy the skill folder (.claude/skills/decide in Abilityai/cornelius) into .agents/skills/decide in your project. Codex loads it when a task matches its description.

Can I use Decide 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 Abilityai/cornelius --skill decide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/decide, .gemini/skills/decide, .github/skills/decide and .opencode/skills/decide in your project.

What does Decide need to run?

SKILL.md names no scripts, command-line tools or credentials: Decide is instructions for the agent only. Its frontmatter pre-approves these tools: Bash, Read, Grep, Glob.

Does Decide access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Decide safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Decide use?

Decide 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 Decide use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Decide?

Skills that share tags, products or a category with Decide: .NET MAUI Release Readiness (dotnet/maui, 23k stars), Release Validation (Mesh-LLM/mesh-llm, 3.5k stars), Final Release Review (openai/openai-agents-python, 30k stars) and Final Release Review (openai/openai-agents-js, 3.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Decide?

Abilityai (a GitHub organization) maintains it in Abilityai/cornelius, which has 109 GitHub stars. The repository holds 54 skills in this directory. The repository was last updated on October 8, 2026.

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