Borrowing it
Nothing to install: this file belongs to macromania/agentop. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/macromania/agentop/main/.github/skills/feature-docs/SKILL.mdgit clone --depth 1 https://github.com/macromania/agentopWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/macromania/agentop/feature-docs)<a href="https://agentmods.dev/skills/macromania/agentop/feature-docs"><img src="https://agentmods.dev/badge/skills/macromania/agentop/feature-docs/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/macromania/agentop/feature-docs"><img src="https://agentmods.dev/badge/skills/macromania/agentop/feature-docs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00055 | $0.01060 |
| Opus 5.5 | $0.00022 | $0.00424 |
| Sonnet 5.5 | $0.00011 | $0.00212 |
| Haiku 4.5 | $0.00006 | $0.00106 |
Grade A, and why
feature-docs scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Documentation
Create feature documentation pages with screenshots for the AgentOp project.
When to Use This Skill
- Documenting a new feature with a screenshot
- Taking a screenshot of the running Electron app
- Writing a feature description page
- Adding a feature entry to the README
CRITICAL: Required Process
You MUST follow these steps in exact order. Do NOT skip or reorder any step.
The user will get the app into the desired visual state and tell you the feature name. Only then do you proceed.
Step 1 — Capture Screenshot
The user has the app running and showing the feature. Capture the app window:
# Interactive window capture — user clicks the AgentOp window
screencapture -w docs/images/{feature-name}.png
- Use kebab-case for the filename matching the feature name
- Save to
docs/images/ - The
-wflag lets the user click the target window - Wait for confirmation that the screenshot was saved successfully
Step 2 — Read Code to Understand the Feature
This step is NOT optional. You MUST read the actual source code before writing any description.
Search the codebase to find the components, hooks, IPC handlers, state atoms, and backend logic related to the feature. Read them thoroughly.
Where to look:
| Layer | Path | What to look for |
|---|---|---|
| UI Components | apps/electron/src/renderer/components/ |
React components rendering the feature |
| Hooks | apps/electron/src/renderer/hooks/ |
Data fetching, state management for the feature |
| State | apps/electron/src/renderer/state/ |
Jotai atoms related to the feature |
| IPC Handlers | apps/electron/src/main/ipc/ |
Backend handlers the feature calls |
| Agent Logic | apps/electron/src/main/agent/ |
Orchestrator, planner, session logic |
| Shared Logic | packages/shared/src/ |
Database schema, business logic |
| Core Types | packages/core/src/types.ts |
Type definitions for the feature's domain |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 112 lines · 55 tokens per session scan A e6c07ffe565d
feature-docs is a skill published in the GitHub repository macromania/agentop (11 stars, last pushed 7mo ago), licensed MIT. It adds 55 tokens to every session and 1,060 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
feature-docs compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| feature-docsmacromania/agentop | Skill | 11 | 7mo ago | MIT | A | 55 | Claude Code, Codex |
| eval-dataset-designbojieli/ai-agent-book | Skill | 57k | 29d ago | Apache-2.0 | A | 138 | Claude Code, Codex |
| aatmf-t10-confidentiality-breachPurpleAILAB/Decepticon | Skill | 6.5k | 8d ago | Apache-2.0 | A | 39 | Claude Code, Codex |
| mochi-remindkirodotdev/KiroCrew | Skill | 4.8k | yesterday | Apache-2.0 | A | 20 | Claude Code, Codex |
| ensembl-databasesynthetic-sciences/openscience | Skill | 4.3k | 2d ago | Apache-2.0 | A | 45 | Claude Code, Codex |
| ai-musicZJU-REAL/Easel | Skill | 4.5k | 4d ago | Apache-2.0 | A | 161 | Claude Code, Codex |
| skill-news-intelligenceZJU-REAL/Easel | Skill | 4.5k | 4d ago | Apache-2.0 | A | 104 | Claude Code, Codex |