Borrowing it
Nothing to install: this file belongs to open-software-network/os-clovy. 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/open-software-network/os-clovy/main/.agents/skills/os-task-prep/SKILL.mdgit clone --depth 1 https://github.com/open-software-network/os-clovyWrote 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/open-software-network/os-clovy/os-task-prep)<a href="https://agentmods.dev/skills/open-software-network/os-clovy/os-task-prep"><img src="https://agentmods.dev/badge/skills/open-software-network/os-clovy/os-task-prep/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/open-software-network/os-clovy/os-task-prep"><img src="https://agentmods.dev/badge/skills/open-software-network/os-clovy/os-task-prep.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 34 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00130 | $0.01979 |
| Opus 5.5 | $0.00052 | $0.00792 |
| Sonnet 5.5 | $0.00026 | $0.00396 |
| Haiku 4.5 | $0.00013 | $0.00198 |
Grade A, and why
os-task-prep scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Sets `User-Agent: os-platform-agent-skill/1.0` -- the default urllib UA is How it starts
The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
os-task-prep
Productizes the loop: find open Issues -> diagnose against the code -> map
cross-Issue dependencies and blockers -> enrich the Issue on the platform ->
(optionally) assign -> emit repo-build-pr prompts so autonomous ("AFK")
agents can pick them up with full context.
It composes two existing skills and adds the one capability they lack:
os-platform(read-only +issues take): list/show Issues, and assign.repo-build-pr: the per-Issue implementation loop the emitted prompts target. Invoke it directly (/repo-build-pr); the old/buildalias is deprecated -- do not emit it.scripts/enrich_issue.py(this skill): the only mutationos-platformdoes not provide --PATCH /v1/orgs/{org}/bounties/{number}to append diagnosis notes tobody_markdown, idempotently and append-only.
Prerequisites
OS_PLATFORM_API_KEYmust be set in the environment (see theos-platformskill). Never ask the user to paste it into chat; never echo it.- Run from a checkout of
open-software-network/os-clovyso the diagnosis step can read the real code. - The default org/project come from
os-platform.json(org,limit).
Workflow
1. Find ready-to-code Issues
Use the os-platform skill. Default to the narrowest actionable queue:
python3 .claude/skills/os-platform/scripts/os_platform.py issues list <org> --status todo --limit 30
Pick candidates that are genuinely ready to code, not just status: todo:
- Prefer
creator.kind: "integration"/ well-specified reports with clear expected behavior over rawcreator.kind: "user"reports that need triage. - Prefer tight, self-contained scope. Flag overlap: Issues that touch the same
large file (e.g.
AgentWorkspace.tsx) will conflict if run in parallel worktrees -- note which to serialize. - Skip design-only / question / vague Issues unless asked.
- Honor assignment hints: surface unassigned or already-yours first.
State how many you selected and why; log anything you dropped.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 170 lines · 130 tokens per session scan A c2a63b444c75
os-task-prep is a skill published in the GitHub repository open-software-network/os-clovy (356 stars, last pushed 2d ago), licensed MIT. It adds 130 tokens to every session and 1,979 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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