Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add termio-sh/termio --skill issue-creatorgit clone --depth 1 https://github.com/termio-sh/termioWrote 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/termio-sh/termio/issue-creator)<a href="https://agentmods.dev/skills/termio-sh/termio/issue-creator"><img src="https://agentmods.dev/badge/skills/termio-sh/termio/issue-creator/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/termio-sh/termio/issue-creator"><img src="https://agentmods.dev/badge/skills/termio-sh/termio/issue-creator.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 84 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 | $0.00096 | $0.01441 |
| Opus 5.5 | $0.00038 | $0.00576 |
| Sonnet 5.5 | $0.00019 | $0.00288 |
| Haiku 4.5 | $0.00010 | $0.00144 |
Grade A, and why
issue-creator 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 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.
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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vague user request → actionable GitHub issue
Preserve the user's voice, identify the underlying problem, add only grounded repository context, and create the smallest honest issue that moves the work forward. Never turn missing information into confident requirements.
Workflow
1. Normalize the raw input
Handle all three input modes:
- Pasted text: preserve the most useful original sentence verbatim.
- Screenshot: inspect both visible text and UI context. Transcribe only what
is legible and mark uncertainty. Keep the original image for
Evidence. - Mixed: treat the pasted explanation as context and the screenshot as primary evidence unless they conflict; surface any conflict.
Build a private scratch intake before drafting:
| Field | Extract |
|---|---|
| Actor | Who experiences this? |
| Situation | When and where does it happen? |
| Friction | What is hard, broken, or missing now? |
| Desired outcome | What should the user be able to achieve? |
| Impact | Why does it matter? |
| Explicit constraints | What did the user actually require? |
| Unknowns | What remains unclear? |
Do not force the request into “As a user, I want…” language. Preserve a direct quote when it expresses the pain better than a summary.
If the message is phrased as a question, identify the latent need but first check whether existing behavior or documentation already answers it. Do not file a feature request for something the product already supports.
2. Resolve repository conventions
Use an explicitly named repository; otherwise resolve the current checkout:
gh auth status
gh repo view --json nameWithOwner,defaultBranchRef,visibility,hasIssuesEnabled
gh issue list --state all --limit 10 --json number,title,state,url
rg --files -g 'CONTRIBUTING*' -g '.github/ISSUE_TEMPLATE/**'
Read any relevant issue template or contributing guide. Match the repository's language, headings, title style, and metadata conventions. Do not invent labels, types, milestones, or assignees.
What ships with it
2 files 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 · 174 lines · 96 tokens per session scan A 1db2128064de
issue-creator is a skill published in the GitHub repository termio-sh/termio (548 stars, last pushed today), licensed MIT. It adds 96 tokens to every session and 1,441 once invoked, about $0.0004 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 2026-08-30.
Other skills, from other repositories
create-issue
Draft and submit a GitHub issue from a user idea or bug description, with bilingual body and correct labels.
status
Surfaces the current state of work in gflow-cli. Three variants at different levels of detail: full state (status), next task only (next), active plan identity (active). All variants run scripts/dev/activeplan.py and filter its output to the requested detail level.
hatch3r-board-groom
Ongoing backlog refinement for existing board items. Re-prioritize, reclassify, re-scope, archive stale items, decompose oversized issues, merge duplicates, refresh dependencies, and remediate board health findings.
hatch3r-board-init
Initializes a project board (GitHub Projects V2, Azure Boards, or GitLab Issue Boards) with hatch3r's label taxonomy, status fields, and board structure. Platform detected from hatch.json.
hatch3r-board-shared
Shared context and procedures for all board commands. Provides platform-agnostic board config, label taxonomy, branch conventions, sync enforcement, and tooling directives. Platform-specific details are in commands/board/shared-{platform}.md.
hatch3r-board-refresh
Regenerates the living board overview dashboard from current board state. Scans all open issues, computes health metrics, and updates the meta:board-overview issue.