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 aget-framework/template-advisor-aget --skill aget-propose-skillgit clone --depth 1 https://github.com/aget-framework/template-advisor-agetWrote 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/aget-framework/template-advisor-aget/aget-propose-skill)<a href="https://agentmods.dev/skills/aget-framework/template-advisor-aget/aget-propose-skill"><img src="https://agentmods.dev/badge/skills/aget-framework/template-advisor-aget/aget-propose-skill/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/aget-framework/template-advisor-aget/aget-propose-skill"><img src="https://agentmods.dev/badge/skills/aget-framework/template-advisor-aget/aget-propose-skill.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 | $0.00033 | $0.00869 |
| Opus 5 | $0.00016 | $0.00434 |
| Sonnet 5 | $0.00007 | $0.00174 |
| Haiku 4.5 | $0.00003 | $0.00087 |
Grade A, and why
aget-propose-skill 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 9d 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.
This is a copy
100% identical to aget-propose-skill — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/aget-propose-skill
Create a structured skill proposal before implementation. Follows governance pattern: propose → review → approve → implement.
Purpose
Prevent unreviewed skill proliferation. Forces deliberate consideration of skill purpose, triggers, and design before investing in implementation.
Input
$ARGUMENTS - Skill name or idea description
Execution
Step 1: Gather Information
Collect from user:
- Skill name (must follow
aget-{verb}-{object}pattern) - Purpose - What problem does this skill solve?
- Triggers - What user actions/phrases should invoke it? (minimum 2)
- Category - Governance, Creation, Monitoring, Learning, Planning, Fleet Ops?
- Scope - Universal (all agents) or Agent-specific?
Step 2: Validate Constraints
C1: Name Format
Pattern: aget-{verb}-{object}
Valid: aget-check-evolution, aget-record-lesson
Invalid: healthcheck-evolution, aget_record_lesson, myskill
C2: Uniqueness
# Check if skill already exists
test -d .claude/skills/$SKILL_NAME && echo "EXISTS" || echo "OK"
C3: Minimum Triggers
Triggers provided >= 2
If any constraint fails, report error and stop.
Step 3: Create Proposal
Create file at planning/skill-proposals/PROPOSAL_{name}.md:
# Skill Proposal: {name}
**Date**: {YYYY-MM-DD}
**Author**: {agent}
**Status**: PROPOSED
---
## Summary
**Name**: {name}
**Category**: {category}
**Scope**: {Universal/Agent-specific}
## Purpose
{What problem does this solve?}
## Triggers
When user says:
- "{trigger 1}"
- "{trigger 2}"
- ...
## Design Notes
{Initial design considerations}
## Dependencies
{Other skills or resources needed}
## Approval
- [ ] Principal reviewed
- [ ] Design approved
- [ ] Ready for implementation
---
*Use `/aget-create-skill {name}` to implement after approval.*
Step 4: Update Index (if exists)
If planning/skill-proposals/INDEX.md exists, add entry.
Step 5: Report
Proposal created: planning/skill-proposals/PROPOSAL_{name}.md
Next steps:
1. Review proposal with principal
2. Get approval
3. Run /aget-create-skill {name} to implement
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.
- 9d ago First seen · 152 lines · 33 tokens per session scan A 473a0d2e29fe
aget-propose-skill is a skill published in the GitHub repository aget-framework/template-advisor-aget (2 stars, last pushed 9d ago), licensed Apache-2.0. It adds 33 tokens to every session and 869 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to aget-propose-skill, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
pipefy-skill-template
Copy this file when authoring a new Pipefy skill. Replace placeholders, then rename the folder so it matches the frontmatter name.
opencli-sitemap-author
Use when creating or maintaining OpenCLI site sitemaps: agent-facing navigation, page-state, action, workflow, API-reference, pitfall, and fallback knowledge for a website. Use after browser exploration discovers durable site context, when a sitemap is stale, or when promoting local site knowledge into the repo.
feishu
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.
interview
Ask one useful structured question at a time only when material product/implementation choices are genuinely missing; remember answers and produce a brief/spec. Discoverable facts should be investigated instead of asked.
recipe-create-meet-space
Create a Google Meet meeting space and share the join link.
atmos-validation
Validate Atmos projects, components, arbitrary JSON Schema inputs, EditorConfig, and GitHub Actions; use affected-file selection and native CI annotations.