decide
Skill1 starsChanged 2 months agoMITView on GitHub
Explores a problem, its context, and possible solutions before someone makes a significant decision. Use when the user invokes /decide, is uncertain about a direction, has not yet evaluated their options, or wants help thinking through a problem. This skill covers the exploration phase. To record a decision that is ready for review, or that the team already adopted, use /log-decision.
51 other projects use a version of this.
Adopted by
Most recently taken up by
- aditya-vermax/skillstheir own version, first seen Nov 8, 2026
- vimkim/my-skillstheir own version, first seen Nov 8, 2026
- yuri-xyz/skillstheir own version, first seen Nov 8, 2026
- blamechris/chroxytheir own version, first seen Nov 8, 2026
- dirien/yet-another-agent-harnesstheir own version, first seen Nov 8, 2026
- Integralist/agent-skillstheir own version, first seen Nov 6, 2026
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Other versions51 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 51
- ParadevAI/Paradev★ 16ksame name
- superset-sh/superset★ 16ksame name
- coreyhaines31/makerskills★ 893same name
- me2resh/apexyard★ 542same name
- menkesu/awesome-pm-skills★ 441same name
- BlockRunAI/blockrun-mcp★ 389same name
- kv0906/pm-kit★ 138same name
- Abilityai/cornelius★ 109same name
- me2resh/agent-decision-record★ 48same name
- seandavi/lifeos-template★ 46same name
41 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository20 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- plugin-versioningSkill
- skill-authoringSkill
- review-skillSkill
- tune-agent-docsSkill
- define-behaviorSkill
- implement-scenariosSkill
- review-feature-suiteSkill
- address-pr-commentsSkill
- code-review-pyramidSkill
- pr-reviewSkill
- review-changesSkill
- backfill-decisionsSkill
- log-decisionSkill
- paretoSkill
- team-topologiesSkill
- standard-firstSkill
- update-branchSkill
- triage-work-itemSkill
- work-itemSkill
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 50 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 16
When the user invokes /decide with an argument, use $ARGUMENTS as the opening topic.
- Distinctive: line 50
Before you evaluate the options that the user already has in mind, push for breadth:
- Distinctive: line 81
One question at a time: Never present a wall of questions.
“Common” is measured: kept by at least 6 in 10 of the 50 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Decide
Help the user think through a significant decision. Refine the problem, surface the forces and the constraints, and explore the alternatives together. This is a conversation between thinking partners, not a form to fill in. Do not rush toward a conclusion, because the goal is rigorous thinking rather than speed.
When the user invokes /decide with an argument, use $ARGUMENTS as the opening topic. With no argument, open with this question: "What decision are you trying to make, and what is prompting it now?"
Phase 1: Frame the problem
Help the user state the problem sharply and honestly. Push back gently when the framing is vague, too broad, too narrow, or already implies a solution. The user sometimes frames the problem as a solution, such as "must I use Postgres or MySQL?". Zoom out first, and ask what the underlying data problem is.
Draw on these probing questions as you need them. Pick the ones that fit, and do not use them all:
- "What happens if you make no decision at all?"
- "Is what you described the root problem, or a symptom of something deeper?"
- "Who is affected by this, and how?"
- "What does success look like? How will you know that you made the right call?"
- "Are you solving this problem, or a problem that you think causes this problem?"
- "Are there relevant code areas, issues, or prior decisions that give context I must look at?"
Once the problem feels well framed, reflect it back in one or two sentences, and confirm it before you move on. If the user reframes it, update your summary.
Phase 2: Forces and constraints
Explore what shapes the decision space. Work through these clusters one at a time, not all at once, and reflect back what you hear after each one:
| Cluster | What to explore |
| Hard constraints | The non-negotiables: regulatory, financial, time, team capability, existing commitments |
| Soft constraints | Preferences or norms that feel fixed, and that the right option can challenge |
| Assumptions | Things taken for granted that can turn out to be false |
| Stakeholders | Whose buy-in the decision needs, and what each of them cares about most |
| Reversibility | What it costs to undo this in 6 months, and in 2 years |
Name a tension between constraints out loud. For example: "You need low cost and high reliability. Those often pull in opposite directions. Which one wins if you have to choose?"
Summarize the forces and the constraints, and confirm them before you move to alternatives.
Phase 3: Generate and evaluate alternatives
Before you evaluate the options that the user already has in mind, push for breadth:
"Before we assess the options you are already considering, let us make sure that we missed nothing. What is the most conservative path? What is the most radical one? What would you do if cost, time, and skill were not constraints?"
Then work through each option, including the ones the user brought, with this structure:
- A brief description.
- What the option serves well.
- What it gives up, or makes harder.
- Which assumptions it depends on.
Play devil's advocate for every option, including the one the user seems to favor. Challenge a weak pro, and surface an underweighted con. When an option is dominated, which means it holds no real advantage over another, say so directly instead of treating every option as equally viable.
Phase 4: Converge
Once the user reaches a clear preference, or enough clarity to decide, summarize the thinking:
- Problem: [one sentence]
- Key constraints: [bullet list]
- Options considered: [names only]
- Leading option: [name plus the core reason]
- Main trade-off accepted: [what the user accepts or sacrifices]
- References: [links to relevant code, issues, prior DRs, or external resources. Omit this line when there are none.]
Confirm the summary with the user, then ask:
"Would you like to log this as a decision record?"
If the user says yes, go straight into the workflow of the log-decision skill. Do not ask the user to type a command. Use the title derived from the decision summary as the DR title. Carry the context of this conversation forward: the problem statement, the forces, the options, the leading option, and the trade-off. Then nobody asks the user again for what this conversation already established.
Principles
- One question at a time. Never present a wall of questions. Ask, listen, reflect, then ask the next thing.
- Produce no document. This skill produces clarity.
/log-decisionproduces the document.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

