Agent skill

Show Your Work

by fmflurry in fmflurry/settings-opencode

Keep a reviewable decision trail for long-running or unattended work: a TSV log with one row per decision (what, why, evidence, result).

MITAuto-check passedDocuments & Office

Install Show Your Work

skills CLI
$ npx skills add fmflurry/settings-opencode --skill show-your-work -a claude-code

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

GitHub CLI
$ gh skill install fmflurry/settings-opencode show-your-work --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/fmflurry/settings-opencode.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/show-your-work .claude/skills/show-your-work && 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
show-your-work
GitHub stars
171
Token cost
~1.8k tokens
SKILL.md length
952 words
Files
3 (incl. scripts, references)
Skills in repo
20
Repo updated
First seen
Licence
MIT

At a glance

Keep a reviewable decision trail for long-running or unattended work: a TSV log with one row per decision (what, why, evidence, result).

  • /show-your-work
  • SKILL.md covers The format, Logging a row, Where it lives and Rules, plus 4 more sections
  • Runs Shell scripts from its folder; calls opencode
  • Multi-phase runs

What it does

Show Your Work is an agent skill from fmflurry/settings-opencode. Keep a reviewable decision trail for long-running or unattended work: a TSV log with one row per decision (what, why, evidence, result). Local by default; commit it when a reviewer needs the trail to trust the result. Use for /show-your-work, autonomous or multi-phase runs, or work a human reviews after stepping away.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts and reference files (for example `scripts/log.sh`).

It sits in Documents & Office, covering CSV and tabular files. The repository describes itself as: Custom OpenCode settings. The licence is MIT.

When your agent uses it

  • /show-your-work
  • Multi-phase runs
  • Work a human reviews after stepping away

Example prompts

  • “/show-your-work”

Requirements

  • A Bash shell

What it can do on your machine

Read from SKILL.md and the folder at commit 0e6c33c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • opencode

    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

Show Your Work loads about 1.8k tokens when it runs, and up to ~1.8k if it reads all its reference files. Until then it costs about 84 tokens; SKILL.md has 952 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~84
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.8k

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 passed

The automated check found no risky patterns in SKILL.md.

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); the scripts in this folder are not scanned.

SKILL.md

The full file from fmflurry/settings-opencode at commit 0e6c33c, republished under its MIT licence (© fmflurry). 952 words, ~1,769 tokens.

Download SKILL.mdSave it as .claude/skills/show-your-work/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
show-your-work
description
Keep a reviewable decision trail for long-running or unattended work: a TSV log with one row per decision (what, why, evidence, result). Local by default; commit it when a reviewer needs the trail to trust the result. Use for /show-your-work, autonomous or multi-phase runs, or work a human reviews after stepping away.

Show your work

If the current project has .claude/skills/show-your-work/SKILL.md or .opencode/skills/show-your-work/SKILL.md, read it and its references/; project specifics override this generic version.

Keep one canonical log.

The format

A single TSV file, one row per decision. Cells stay single-line. Evidence is a pointer, not prose.

Copy references/decision-log-template.tsv (the header row) to start a clean log. Columns:

  • ts. ISO8601 timestamp.
  • phase. The phase or workstream.
  • decision. What was chosen or done, one line.
  • why. The reason in plain words. If a principle drove it, say it plainly, not as a jargon tag.
  • evidence. A link or path that proves it: commit SHA, PR number, file:line, or an artifact, trace, or screenshot path. Never a paragraph.
  • result. The outcome or predicate state: tests green, reverted, pixel-diff 0, INCONCLUSIVE, open.

An example, plain-spoken so a reviewer reads it at a glance.

ts	phase	decision	why	evidence	result
2026-05-24T09:02:00Z	frame	counted the work first, about 100 components and roughly 75 hours	wanted to know the size before starting a long run	commit 3a9f1c2	found 5 things to sort out before starting
2026-05-24T09:40:00Z	harness	took screenshots of the old version before changing anything	so we can compare old against new and catch any visual change	scripts/snapshot.sh, baseline/	saved 120 reference screenshots
2026-05-24T11:15:00Z	widget	moved the widget styles over without changing how it looks	keep the change small and the result identical	commit 7c21e0a, pixel-diff 0	looks identical, tests pass
2026-05-24T12:30:00Z	widget	threw out a helper's work because its screenshots were blank	checked the real files instead of trusting its summary	worktree reset	reverted, tightened the instructions for next time

Logging a row

Write each entry the way you'd tell a teammate what you did. Plain words, concrete actions, no AI speak or abstract jargon ([[humanizer]] applies to log text too).

The helper is .claude/skills/show-your-work/scripts/log.sh (Claude) or .opencode/skills/show-your-work/scripts/log.sh (OpenCode). Use it as log.sh <logfile> <phase> <decision> <why> <evidence> <result>. It stamps ts, writes the header on first use, strips stray tabs/newlines, and prefixes any cell starting with =, +, -, or @ with a single quote. A bare printf appending a row works too, but mind those same bytes if cells come from generated or user-supplied text.

Log decision points and checkpoints, not every action: a fork chosen, a unit completed with its verification result, a pivot or revert with its trigger, a blocker surfaced, a gate fixed. For loop runs, one row per iteration. Skip the trivial and self-evident.

A run is one agent conversation, including its later turns and any summary of it. A pickup, a replacement agent, or a new chat starts a new run. When a run adds to a log that already has rows, its first row has phase start, and so does its first row after another run's start row. So a run that comes back to a log in a later turn first reads the log's last rows to see whether another run wrote since. A start row names the ts range of the rows before it that this run did not write, and its evidence names this run, such as its agent id. Use phase start for nothing else.

Where it lives

By default the log is a working artifact, not committed. Keep it at decisions.tsv in the work dir, or .audit/<task-slug>.tsv when several efforts run at once, and leave it out of git.

Commit it only when the work is ambitious enough that a reviewer needs the trail to trust the result.

Rules

  • Append-only. A wrong call gets a new row that supersedes it. Never edit or delete history.
  • Prefer evidence produced by committed scripts over hand-made one-offs.
Show full SKILL.md (481 more words)Show less

Audit the log against the transcript

At the end of the run, before handing back, check the log told the truth. Read this run's transcript, this project only:

  • Claude Code: the newest *.jsonl under ~/.claude/projects/<cwd-slug>/. Never glob across other project directories; that reads unrelated private chats.
  • OpenCode: opencode session list to find this run's session, then opencode export <id>.
  • If neither is available, audit against your own context and say so in the reply.

Walk this run's rows against what actually happened. Each stretch of them begins at one of this run's start rows, or at the first row if this run created the log, and ends at the next start row of another run:

  • Check that every row maps to a real decision or action.
  • Check that each row's evidence resolves and shows what the row claims.
  • A fork, pivot, or abandoned approach that shaped the work but isn't logged is a gap. Add it.

Correct the log, not the story. The audit never edits or removes a row, even an invented one. When a row records neither a real decision nor a real action, or its claim or evidence is wrong, add a row that supersedes it with what actually happened and a pointer that resolves. This audit does not check rows outside this run's stretches. If this run's own work shows one of them is wrong, supersede it like any wrong call.

Cross-model review of the trail

Before handing back, spawn a reviewer subagent, on a different model than the one that did the work when the harness allows it. Self-review is not a substitute. Claude Code only spawns Claude models, so the reviewer there is the same family. OpenCode can use an agent bound to a different OPENCODE_MODEL_*. The subagent reads the audit trail and the run's transcript, then flags what the user should pay attention to. Not a redo of the work, a scan for what's suboptimal or risky.

  • Decisions logged with weak or absent evidence.
  • Verification steps skipped or claimed without proof in the transcript.
  • Choices that look risky in hindsight (premature, scope-creeping, papering over a symptom).
  • Gaps the user would otherwise miss on a casual skim.

Every reply for a run that produced a trail ends with an "Attention" section. Lead with the reviewer's model on its own line (reviewed by <model>, or reviewed by <model> (same family) when it matches the worker), then list each flag pointing to specific rows or moments. "No flags" is a valid value. The model name is not: never fake it.

Reviewing the trail

Read top to bottom, follow the evidence pointers, spot-check. GitHub renders a committed TSV as a table. column -s$'\t' -t decisions.tsv renders it in a terminal.

Composing this skill

Other skills route their audit trail here instead of inventing one. Reference it by name and let it own the format. Don't restate the columns.

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

Files

SKILL.md and 2 other files (scripts, references) in skills/show-your-work of fmflurry/settings-opencode.

  • SKILL.md
  • references/decision-log-template.tsv
  • scripts/log.sh

Open the folder on GitHubat commit 0e6c33c

Compare with similar skills

Show Your Work 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.

Show Your Work compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Show Your Work this skillfmflurry/settings-opencode171—~1.8kAutomated safety check: PassMIT
Data Table Managern8n-io/n8n207k—~2.3kAutomated safety check: PassCustom licence
Instrument Data To Allotropeaws-samples/amazon-bedrock-agents-healthcare-lifesciences2742 repos~2.7kAutomated safety check: PassApache-2.0
Abuse Hunternexu-io/harness-engineering-guide664—~1.9kAutomated safety check: PassMIT
Markitshift-labs-ai/markit1.3k—~299Automated safety check: PassMIT
Sector Analysttradermonty/claude-trading-skills3k1 repos~2.3kAutomated safety check: PassMIT

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Questions about Show Your Work

What does Show Your Work do?

Keep a reviewable decision trail for long-running or unattended work: a TSV log with one row per decision (what, why, evidence, result). Show Your Work is an agent skill from fmflurry/settings-opencode. Keep a reviewable decision trail for long-running or unattended work: a TSV log with one row per decision (what, why, evidence, result).

When should I use Show Your Work?

Show Your Work fits situations like: /show-your-work; multi-phase runs; work a human reviews after stepping away.

How do I install Show Your Work in Claude Code?

Run `npx skills add fmflurry/settings-opencode --skill show-your-work -a claude-code`. Or copy the skill folder (skills/show-your-work in fmflurry/settings-opencode) into .claude/skills/show-your-work in your project. Claude Code loads it when a task matches its description.

How do I install Show Your Work in Codex?

Run `npx skills add fmflurry/settings-opencode --skill show-your-work -a codex`. Or copy the skill folder (skills/show-your-work in fmflurry/settings-opencode) into .agents/skills/show-your-work in your project. Codex loads it when a task matches its description.

Can I use Show Your Work 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 fmflurry/settings-opencode --skill show-your-work -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/show-your-work, .gemini/skills/show-your-work, .github/skills/show-your-work and .opencode/skills/show-your-work in your project.

What does Show Your Work need to run?

Going by SKILL.md and its folder, Show Your Work needs a shell for the scripts in its folder and the command-line tools its instructions call (opencode). Our summary lists: A Bash shell.

Does Show Your Work 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 Show Your Work safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Show Your Work use?

Show Your Work 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 Show Your Work use?

About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 10 tokens, read only when the agent opens those files.

What are the alternatives to Show Your Work?

Skills that share tags, products or a category with Show Your Work: Data Table Manager (n8n-io/n8n, 207k stars), Instrument Data To Allotrope (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars), Abuse Hunter (nexu-io/harness-engineering-guide, 664 stars) and Markit (shift-labs-ai/markit, 1.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Show Your Work?

fmflurry (a GitHub user) maintains it in fmflurry/settings-opencode, which has 171 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on October 7, 2026.

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