Show Me Your Work Decision Log
cursor/plugins
Keeps a TSV decision log for long or unattended agent runs, one row per decision with what, why, evidence and result, so a reviewer can check the work later.
A skill your agent uses when you finish an analiz report - the human must approve the analysis before any implementation task is created, via the analizreview column
$ npx skills add makifbaysal/tasktrooper --skill analiz-human-review-gate -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install makifbaysal/tasktrooper analiz-human-review-gate --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/makifbaysal/tasktrooper.git skills-src && mkdir -p .claude/skills && cp -r skills-src/catalog/agents/system-architect/skills/analiz-human-review-gate .claude/skills/analiz-human-review-gate && rm -rf skills-srcUse ~/.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/
Install the "analiz-human-review-gate" agent skill from https://github.com/makifbaysal/tasktrooper/tree/main/catalog/agents/system-architect/skills/analiz-human-review-gate into .claude/skills/analiz-human-review-gate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analiz-human-review-gate", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/makifbaysal/tasktrooper/tree/main/catalog/agents/system-architect/skills/analiz-human-review-gateType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add makifbaysal/tasktrooper --skill analiz-human-review-gate -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install makifbaysal/tasktrooper analiz-human-review-gate --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/makifbaysal/tasktrooper.git skills-src && mkdir -p .agents/skills && cp -r skills-src/catalog/agents/system-architect/skills/analiz-human-review-gate .agents/skills/analiz-human-review-gate && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "analiz-human-review-gate" agent skill from https://github.com/makifbaysal/tasktrooper/tree/main/catalog/agents/system-architect/skills/analiz-human-review-gate into .agents/skills/analiz-human-review-gate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analiz-human-review-gate", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add makifbaysal/tasktrooper --skill analiz-human-review-gate -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install makifbaysal/tasktrooper analiz-human-review-gate --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/makifbaysal/tasktrooper.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/catalog/agents/system-architect/skills/analiz-human-review-gate .cursor/skills/analiz-human-review-gate && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "analiz-human-review-gate" agent skill from https://github.com/makifbaysal/tasktrooper/tree/main/catalog/agents/system-architect/skills/analiz-human-review-gate into .cursor/skills/analiz-human-review-gate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analiz-human-review-gate", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/makifbaysal/tasktrooper.git --path catalog/agents/system-architect/skills/analiz-human-review-gate--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add makifbaysal/tasktrooper --skill analiz-human-review-gate -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install makifbaysal/tasktrooper analiz-human-review-gate --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/makifbaysal/tasktrooper.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/catalog/agents/system-architect/skills/analiz-human-review-gate .gemini/skills/analiz-human-review-gate && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "analiz-human-review-gate" agent skill from https://github.com/makifbaysal/tasktrooper/tree/main/catalog/agents/system-architect/skills/analiz-human-review-gate into .gemini/skills/analiz-human-review-gate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analiz-human-review-gate", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install makifbaysal/tasktrooper analiz-human-review-gateInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add makifbaysal/tasktrooper --skill analiz-human-review-gate -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/makifbaysal/tasktrooper.git skills-src && mkdir -p .github/skills && cp -r skills-src/catalog/agents/system-architect/skills/analiz-human-review-gate .github/skills/analiz-human-review-gate && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "analiz-human-review-gate" agent skill from https://github.com/makifbaysal/tasktrooper/tree/main/catalog/agents/system-architect/skills/analiz-human-review-gate into .github/skills/analiz-human-review-gate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analiz-human-review-gate", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add makifbaysal/tasktrooper --skill analiz-human-review-gate -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install makifbaysal/tasktrooper analiz-human-review-gate --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/makifbaysal/tasktrooper.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/catalog/agents/system-architect/skills/analiz-human-review-gate .opencode/skills/analiz-human-review-gate && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "analiz-human-review-gate" agent skill from https://github.com/makifbaysal/tasktrooper/tree/main/catalog/agents/system-architect/skills/analiz-human-review-gate into .opencode/skills/analiz-human-review-gate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analiz-human-review-gate", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
analiz-human-review-gateA skill your agent uses when you finish an analiz report - the human must approve the analysis before any implementation task is created, via the analizreview column
Analiz Human Review Gate is an agent skill from makifbaysal/tasktrooper. Use when you finish an analiz report - the human must approve the analysis before any implementation task is created, via the analizreview column
Its SKILL.md is about 2.2k 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 Agent Workflows, covering Human-in-the-loop approvals. The repository describes itself as: Local-first agent platform: board + role agents + agent CLI runs (Claude Code, Cursor, Antigravity, OpenCode) or local and API models (Ollama, LM Studio), all on your own Mac. The licence is Apache-2.0.
2 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit c4496d5. It shows what the files ask for, not the result of running them.
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.
No scripts in the folder and no shell commands in SKILL.md (its code samples are dot).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Analiz Human Review Gate loads about 2.2k tokens when it runs. Until then it costs about 43 tokens; SKILL.md has 1,087 words of instructions outside code blocks.
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.
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); files beside SKILL.md are not scanned.
The full file from makifbaysal/tasktrooper at commit c4496d5, republished under its Apache-2.0 licence (© makifbaysal). 1,087 words, ~2,174 tokens.
.claude/skills/analiz-human-review-gate/SKILL.md (or your agent's skills folder).Your analysis output — the ONE analysis report, with the spec and the implementation plan as its sections — is not self-approved. A human reviews it BEFORE any implementation task exists. This is the only human gate in the system: the human does not review individual dev tasks, but they DO review your plan, because a wrong plan multiplies into wrong tasks across every project.
The human reviews the report passage by passage: they select text in it, comment on it, and send all their comments back at once. Each comment is anchored to the words it is about, so it is precise — and every one of them needs an answer.
Core principle: No implementation task is created from an unapproved plan. You stop, the task waits at analiz_review, and you create nothing until the human approves.
This reverses the old flow. You no longer create tasks and then close the analiz. You present the plan, wait for approval, and only THEN create tasks.
digraph gate {
"Report written\n& self-reviewed" [shape=box];
"Summary comment, STOP\n(system moves -> analiz_review)" [shape=box];
"Human decision" [shape=diamond];
"Human moves -> done\n(approved)" [shape=box];
"Human sends comments\n-> need_revision (rejected)" [shape=box];
"Create per-project impl tasks\n+ list them" [shape=box];
"Move analiz -> released" [shape=doublecircle];
"Fix every comment at root\nin the SAME report, resolve each\n(system moves -> analiz_review)" [shape=box];
"Report written\n& self-reviewed" -> "Summary comment, STOP\n(system moves -> analiz_review)";
"Summary comment, STOP\n(system moves -> analiz_review)" -> "Human decision";
"Human decision" -> "Human moves -> done\n(approved)" [label="approve"];
"Human decision" -> "Human sends comments\n-> need_revision (rejected)" [label="request changes"];
"Human moves -> done\n(approved)" -> "Create per-project impl tasks\n+ list them";
"Create per-project impl tasks\n+ list them" -> "Move analiz -> released";
"Human sends comments\n-> need_revision (rejected)" -> "Fix every comment at root\nin the SAME report, resolve each\n(system moves -> analiz_review)";
"Fix every comment at root\nin the SAME report, resolve each\n(system moves -> analiz_review)" -> "Human decision";
}When the report is written, self-reviewed, and attached via add_task_document (format: "html", analiz-html-report):
add_task_comment — a review-ready summary for the human:analiz: …).You are re-dispatched (as the analiz task's assignee) when the human decides. The task's current column tells you which path:
Column is done → APPROVED.
list_open_questions if the context block doesn't already show them). An unanswered non-blocking question means its recommended_answer stands. If a human's answer contradicts the approved split or plan in a way this decomposition cannot absorb, do NOT decompose — add_task_comment naming the conflict and stop (open-questions-protocol).derived_from: ["<this analiz task's key>"]. Your report — spec and plan — is a document on THIS task and exists nowhere else — the reference is what puts it in front of the developer and what makes list_task_documents able to return it. A task without it is a task whose specification cannot be found.blocked_by (who codes first) and deploy_depends_on (who ships first), not in the description.add_task_comment listing every created task: title, assignee, project, and its order.move_board_task the analiz task to released. You are finished.The run is a revision (the task came back through need_revision) → REJECTED.
list_document_annotations with status submitted returns every one. Also read the task comments: the review's covering note is there.list_task_documents on this task with the report's document_id and raw: true; follow next_offset until you have all of it.list_open_questions if you need the full list): fold the answer into the report and withdraw or replace any question it made moot. An unanswered non-blocking question means its recommended_answer stands — do not re-ask it (open-questions-protocol).update_task_document on its document_id — edits (each old_text copied exactly from the source) for targeted passages, content for a rewrite. Keep its sections and ids, and keep its TITLE unchanged (a new date creates a second document instead of revising this one). Never attach a second document. Leave split as the human approved unless a comment or a code re-read gives you a concrete reason to change it.resolve_document_annotations ONCE, with {id, reply} for every comment you were sent: the reply is one line saying what changed and where ("Replaced the queue with a cron job — see #design and #step-2"), or why you deliberately kept it.add_task_comment with a short summary of what changed. Then STOP: when the run ends with the report revised, the system moves the task back to analiz_review — do not move it yourself.analiz_review, done or need_revision — the system moves it to analiz_review, and done / need_revision are the human's decisions. You move it only to released, after approval.update_task_document.analiz_review → you are creating tasks before approval.derived_from → they point at no analysis, and the report you spent the run writing is unreachable from the work it specifies.move_board_task to analiz_review or done → that is the system's move or the human's, not yours.add_task_document during a revision → revise the existing report with update_task_document instead.© makifbaysal, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in catalog/agents/system-architect/skills/analiz-human-review-gate of makifbaysal/tasktrooper.
Open the folder on GitHubat commit c4496d5
Analiz Human Review Gate 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Analiz Human Review Gate this skillmakifbaysal/tasktrooper | 112 | — | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| Show Me Your Work Decision Logcursor/plugins | 11k | 8 repos | ~1.6k | Automated safety check: Pass | None | |
| Darwin Skill Optimizeralchaincyf/darwin-skill | 6.2k | 1 repos | ~4.7k | Automated safety check: Pass | MIT | |
| Loop Constraints Enforcercobusgreyling/loop-engineering | 11k | 1 repos | ~475 | Automated safety check: Notes | MIT | |
| Ask User QuestionMemTensor/MemOS | 12k | — | ~1k | Automated safety check: Pass | Apache-2.0 | |
| PUA High-Agency Governancetanweai/pua | 20k | — | ~502 | Automated safety check: Pass | MIT |
cursor/plugins
Keeps a TSV decision log for long or unattended agent runs, one row per decision with what, why, evidence and result, so a reviewer can check the work later.
alchaincyf/darwin-skill
Scores SKILL.md files on a nine-dimension rubric, then improves them in a keep-or-revert loop with independent judge agents, test prompts, git history and human checkpoints.
cobusgreyling/loop-engineering
Loads a project's loop-constraints.md before any other action and blocks pushes, edits or merges that violate the rules it defines.
MemTensor/MemOS
Shows a question as a modal in the interface to clarify a task, collect a preference or get approval, since the user cannot see terminal output.
tanweai/pua
Pushes an agent to keep verifying and changing approach after repeated failures, using a diagnosis line, evidence-based completion and confirmation before risky edits.
rohitg00/agentmemory
Deletes chosen memories from agentmemory only after showing the matches and getting an explicit yes, for privacy requests and cleanup of outdated notes.
makifbaysal/tasktrooper
A skill your agent uses when writing acceptance criteria for a task - express each as an observable Given/When/Then that QA can execute, including negative cases
makifbaysal/tasktrooper
A skill your agent uses when the diff adds or changes an endpoint, resolver, RPC, job or query that takes an object id, a role check, a request binding or a tenant filter - BOLA/IDOR, function-level…
makifbaysal/tasktrooper
A skill your agent uses when a task changes any screen, form, dialog, menu or control - Lighthouse/axe scan of the changed screens, a keyboard walk, and the thresholds that fail a task
makifbaysal/tasktrooper
A skill your agent uses when deciding whether a request needs an analiz task before implementation - the conditions that require the architect's analysis versus going straight to implementation
makifbaysal/tasktrooper
A skill your agent uses when you write or revise the analiz deliverable - the ONE self-contained HTML report (spec and plan as sections) a human reviews passage by passage
makifbaysal/tasktrooper
A skill your agent uses when building native Android with Jetpack Compose - stateless composables, state hoisting, ViewModel-owned state, edge-to-edge, predictive back, adaptive layout, atomic…
Categories
A skill your agent uses when you finish an analiz report - the human must approve the analysis before any implementation task is created, via the analizreview column. Analiz Human Review Gate is an agent skill from makifbaysal/tasktrooper.
Analiz Human Review Gate fits situations like: you finish an analiz report - the human must approve the analysis before any implementation task is created; via the analizreview column.
Run `npx skills add makifbaysal/tasktrooper --skill analiz-human-review-gate -a claude-code`. Or copy the skill folder (catalog/agents/system-architect/skills/analiz-human-review-gate in makifbaysal/tasktrooper) into .claude/skills/analiz-human-review-gate in your project. Claude Code loads it when a task matches its description.
Run `npx skills add makifbaysal/tasktrooper --skill analiz-human-review-gate -a codex`. Or copy the skill folder (catalog/agents/system-architect/skills/analiz-human-review-gate in makifbaysal/tasktrooper) into .agents/skills/analiz-human-review-gate in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add makifbaysal/tasktrooper --skill analiz-human-review-gate -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analiz-human-review-gate, .gemini/skills/analiz-human-review-gate, .github/skills/analiz-human-review-gate and .opencode/skills/analiz-human-review-gate in your project.
SKILL.md names no scripts, command-line tools or credentials: Analiz Human Review Gate is instructions for the agent only.
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.
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. Review the folder before installing.
Analiz Human Review Gate is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.2k tokens (SKILL.md is roughly 8.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Analiz Human Review Gate: Show Me Your Work Decision Log (cursor/plugins, 11k stars), Darwin Skill Optimizer (alchaincyf/darwin-skill, 6.2k stars), Loop Constraints Enforcer (cobusgreyling/loop-engineering, 11k stars) and Ask User Question (MemTensor/MemOS, 12k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
makifbaysal (a GitHub user) maintains it in makifbaysal/tasktrooper, which has 112 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on October 10, 2026.
Source: makifbaysal/tasktrooper on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.