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 spencerpauly/skills-repo --skill suggesting-skillsgit clone --depth 1 https://github.com/spencerpauly/skills-repoWrote 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/spencerpauly/skills-repo/suggesting-skills)<a href="https://agentmods.dev/skills/spencerpauly/skills-repo/suggesting-skills"><img src="https://agentmods.dev/badge/skills/spencerpauly/skills-repo/suggesting-skills/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/spencerpauly/skills-repo/suggesting-skills"><img src="https://agentmods.dev/badge/skills/spencerpauly/skills-repo/suggesting-skills.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 | $0.00071 | $0.00781 |
| Opus 5.5 | $0.00028 | $0.00312 |
| Sonnet 5.5 | $0.00014 | $0.00156 |
| Haiku 4.5 | $0.00007 | $0.00078 |
Grade A, and why
suggesting-skills 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Suggesting Skills
Find the gaps in the user's skill library. Skills are most valuable when they capture the things the user would otherwise have to explain to the agent every time.
When to use
- The user explicitly asks "what skills am I missing", "what should I add", "audit my skills".
- You notice the same kind of request happening repeatedly in a session — that's a skill waiting to be written.
- After a long session, before the user closes the chat, offer to extract any reusable playbook from the work just done.
Steps
-
Inventory what's already there. Read every
SKILL.mdin the repo. Note for each: name, the trigger phrase in the description, and the one-line goal. If two existing skills overlap, flag the duplication. -
Look for the pattern of "I keep telling you to…". Strong candidates for new skills are:
- Repeated workflow — the user has asked for the same multi-step task at least twice.
- Repeated correction — the user has had to fix the same kind of mistake the agent makes (formatting, voice, missing a step).
- Tribal knowledge — facts about this user's stack, team, or product that aren't in the codebase but the user keeps having to restate.
- External tool wiring — the user has an MCP, CLI, or API the agent could be using but isn't.
-
Propose 3–5 candidate skills, each as a one-paragraph pitch:
Name: kebab-case-name Trigger: when the user says "..." or asks to "..." What it does: one sentence Why it's worth a skill: the repeated thing it replaces -
Rank them. Sort by frequency × annoyance: how often does the situation come up, and how painful is it when it's not automated?
-
Ask the user which 1–2 to actually write. Don't auto-generate all of them. Skills that aren't trusted get ignored, which is worse than not having them.
-
For each chosen skill, scaffold a
SKILL.mdinskills/<name>/with:- Frontmatter (
name,descriptionwith trigger phrases,license). - "When to use" — the trigger conditions, in plain English.
- "Steps" — numbered, imperative.
- "Don't" — the failure modes you've seen.
- Frontmatter (
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 · 64 lines · 71 tokens per session scan A e4421c70afe0
suggesting-skills is a skill published in the GitHub repository spencerpauly/skills-repo (27 stars, last pushed 4mo ago), licensed MIT. It adds 71 tokens to every session and 781 once invoked, about $0.0003 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.
suggesting-skills compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| suggesting-skillsspencerpauly/skills-repo | Skill | 27 | 4mo ago | MIT | A | 71 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 135k | today | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 100k | today | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 80k | 6d ago | MIT | A | 200 | Claude Code, Codex |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 317k | 9d ago | MIT | A | 21 | Claude Code |