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 tomzx/agents --skill identify-skill-gapsgit clone --depth 1 https://github.com/tomzx/agentsWrote 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/tomzx/agents/identify-skill-gaps)<a href="https://agentmods.dev/skills/tomzx/agents/identify-skill-gaps"><img src="https://agentmods.dev/badge/skills/tomzx/agents/identify-skill-gaps/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/tomzx/agents/identify-skill-gaps"><img src="https://agentmods.dev/badge/skills/tomzx/agents/identify-skill-gaps.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 | $0.00040 | $0.00648 |
| Opus 5.5 | $0.00016 | $0.00259 |
| Sonnet 5.5 | $0.00008 | $0.00130 |
| Haiku 4.5 | $0.00004 | $0.00065 |
Grade A, and why
identify-skill-gaps 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 22d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BASE_DIR=!~/.agents/scripts/get-env NOTES_DIR
Identify Skill Gaps
Surfaces manual workflows that could become skills, then prompts to scaffold or backlog them.
Prerequisites
- agents repository available at
~/agents(for reading the existing skill library) - Optional:
{BASE_DIR}/skill-backlog.md(created if it does not exist when the user chooses backlog) - Optional: activity context from the current session (summaries, standup, review files) to infer today's workflows
Steps
1. Inventory existing skills
List all directories under ~/agents/skills/.
This is the current skill library.
2. Extract workflows from context
From any activity context available in the session (GitHub summary, Slack summary, overall summary, standup, review, or conversation), identify distinct repeated or multi-step workflows the user executed. Focus on:
- Things done more than once, or done the same way as on previous days.
- Multi-step tasks that follow a clear pattern (collect → process → write → send).
- Anything the user said "I always do X when Y" about, explicitly or implicitly.
- Manual steps that produced an artifact (a doc, a message, a PR, a report).
3. Compare against existing skills
For each workflow identified, check if a matching skill already exists in the library. A skill "covers" a workflow if its name or description clearly matches the intent.
4. Report gaps
Present a short bulleted list of workflows that have no matching skill, grouped by rough category (e.g., communication, code review, reporting, planning). For each gap include:
- A one-sentence description of the workflow.
- A suggested skill name (kebab-case).
- Estimated frequency (daily / weekly / ad-hoc).
Example output format:
## Skill Gaps Identified
- **post-incident-summary** — Write and send a structured summary after a production incident. (weekly)
- **changelog-entry** — Draft a changelog entry from a merged PR description. (daily)
- **meeting-prep** — Pull agenda, related PRs, and open issues before a meeting. (ad-hoc)
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.
- 22d ago Changed · +4 lines f4afd399e1c5
- 24d ago Changed 648b8aba1e35
- 1mo ago First seen · 66 lines · 40 tokens per session scan A 785fea2f1ce5
identify-skill-gaps is a skill published in the GitHub repository tomzx/agents (13 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 648 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 2026-09-03.
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