explain-outcome
Use when reporting a failed command, test, build, or deploy, an investigation into an error or incident, or the result of a multi-step task.
Skill by lwlee2608
Chalk Labs
Need help deploying explain-outcome?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/lwlee2608-explain-outcome
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: documents, testing, devops, productivity
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/explain-outcome
What's inside
- Skill name
explain-outcome- Description
- Use when reporting a failed command, test, build, or deploy, an investigation into an error or incident, or the result of a multi-step task. Structures the report as three parts: what happened, what it means, what's next.
- License
- MIT
- Instructions
- 47 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Explain Outcome
Report the result in three parts, in this order. The goal is only this: a human reads it once and understands.
Write in ASD-STE100 Simplified Technical English. Short sentences are easier to read than long ones. The active voice is easier than the passive. One word for one meaning is easier than a synonym each time. Plain words are easier than jargon.
## Format
```
**What happened**
<the facts: what ran, what it returned, what changed>
**What it means**
<the cause, the effect, and what is not known yet>
**What's next**
<the action the agent will do, or the decision the user must make>
```
Facts go under "What happened". Guesses go under "What it means", marked "likely" or "not confirmed". "What's next" is an action: "I will..." or "You must decide...". If no action is necessary, write "Nothing. Done." For a small result with no decision, reply in one sentence instead.
## Worked example
User: *"Run the tests."*
Good:
```
**What happened**
`make test` failed. 1 of 42 tests failed:
FAIL: TestOrderTotal_Discount (order_test.go:88)
expected 90.00, got 100.00
**What it means**
The discount is not in the order total. The likely cause is an early return in `applyDiscount` (order.go:41). This is not confirmed. No other test failed.
**What's next**
- I will read `applyDiscount` to confirm the cause, then fix it.
- You must decide: does a 0% discount call `applyDiscount`, or skip it?
```
Bad — facts and guesses in one sentence, asks instead of states:
> Tests failed because the discount logic is broken in order.go, probably the early return. I can fix it if you want.From lwlee2608/agent-skills, MIT.
More from lwlee2608/agent-skills
- 0.587score
build-feature
lwlee2608
Use when implementing a phased feature plan file.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
gh-create-pr
lwlee2608
Use when creating/raising/opening/submitting a GitHub PR.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
plan-feature
lwlee2608
Use when planning a feature too big to hold in one session.
SkillAFreshness: A★ 1Claude Code +9 - 0.586score
create-skill
lwlee2608
Use when creating a new agent skill.
SkillAFreshness: A★ 1Claude Code +9 - 0.586score
review-code
lwlee2608
Use when asked to review a local diff, a GitHub PR, or a whole codebase.
SkillAFreshness: A★ 1Claude Code +9 - 0.576score
merge-pr
lwlee2608
Merge a GitHub PR, close linked issues, and delete the branch.
SkillAFreshness: A★ 1Claude Code +9 - 0.562score
retro
lwlee2608
Use when the user asks for a retrospective on an agent session ("/retro", "how did this session go", "what could this session do better"), for the current…
SkillAFreshness: A★ 1Claude Code +9 - 0.562score
whoami
lwlee2608
Use when the user asks for the current session's ID (e.g., "/whoami", "what's your session id", "who are you") so another agent session can find or message…
SkillAFreshness: A★ 1Claude Code +9 - 0.562score
second-opinion
lwlee2608
Use when the user asks for a second-opinion review from another agent (e.g., "get a second opinion", "review with pi", "review using gpt-6-astra"…
SkillAFreshness: A★ 1Claude Code +9 - 0.562score
review-loop
lwlee2608
Use only when the user explicitly asks to review and fix in a loop until clean.
SkillAFreshness: A★ 1Claude Code +9 - 0.547score
generate-media
lwlee2608
Use when generating or editing an image or video with an AI model — ads, mockups, style variations, image-to-video.
SkillBFreshness: B★ 1Claude Code +9 - 0.547score
linear-issues
lwlee2608
Use when reading, searching, creating, updating, or commenting on Linear issues.
SkillBFreshness: B★ 1Claude Code +9
Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Sep 15, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/lwlee2608/agent-skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from lwlee2608
- 0.587score
build-feature
lwlee2608
Use when implementing a phased feature plan file.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
plan-feature
lwlee2608
Use when planning a feature too big to hold in one session.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
gh-create-pr
lwlee2608
Use when creating/raising/opening/submitting a GitHub PR.
SkillAFreshness: A★ 1Claude Code +9 - 0.586score
review-code
lwlee2608
Use when asked to review a local diff, a GitHub PR, or a whole codebase.
SkillAFreshness: A★ 1Claude Code +9 - 0.586score
create-skill
lwlee2608
Use when creating a new agent skill.
SkillAFreshness: A★ 1Claude Code +9 - 0.576score
merge-pr
lwlee2608
Merge a GitHub PR, close linked issues, and delete the branch.
SkillAFreshness: A★ 1Claude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get explain-outcome running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
explain-outcome skill. Agent Mart. https://agentmart.dev/skills/lwlee2608-explain-outcome (last updated 2026-10-24)