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 nthnclrk/enablement-skills --skill content-gap-analysisgit clone --depth 1 https://github.com/nthnclrk/enablement-skillsWrote 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/nthnclrk/enablement-skills/content-gap-analysis)<a href="https://agentmods.dev/skills/nthnclrk/enablement-skills/content-gap-analysis"><img src="https://agentmods.dev/badge/skills/nthnclrk/enablement-skills/content-gap-analysis/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/nthnclrk/enablement-skills/content-gap-analysis"><img src="https://agentmods.dev/badge/skills/nthnclrk/enablement-skills/content-gap-analysis.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 | $0.00066 | $0.00919 |
| Opus 5.5 | $0.00026 | $0.00368 |
| Sonnet 5.5 | $0.00013 | $0.00184 |
| Haiku 4.5 | $0.00007 | $0.00092 |
Grade A, and why
content-gap-analysis 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 24d 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content gap analysis
Prioritize content work by the field problem it will solve. Check whether an asset exists, fits the task, can be found, and is used before recommending a new one.
Fails. "Zero views this quarter, so retire the security FAQ."
Passes. "The security FAQ exists, is current, and drew 19 failed searches against 6 views. Action: improve discoverability, not retire. The mid-market ROI template does not exist; the enterprise calculator is out of scope. Action: create."
A recurring operating model for owners, review, and publishing is content-governance-system. Raw field-note synthesis is field-feedback-synthesizer.
Inputs
Ask only for the inputs that change the backlog:
- Inventory source and the roles, stages, and jobs in scope
- Known field requests, failed searches, or usage with an eligible-audience denominator
- Evaluation horizon: this quarter, half, or annual planning
- Who can own create, update, consolidate, or retire work
If usage, ownership, or freshness is unknown, leave it unknown. Do not invent usage or ROI.
Supporting material
Read references/content-gap-prioritization.md for exists-vs-used tests, action types, and scoring rules. Read references/source-system-guide.md when the inventory comes from a content repository, wiki, or field-signal channel.
Procedure
- Build the inventory you can defend. Stable ID, owner, audience, status, last reviewed date, canonical location. Done when each in-scope asset has enough metadata to judge exists vs used.
- Map coverage. Role, stage, job-to-be-done. An enterprise-only asset does not cover a mid-market job.
- Classify the problem before you score it. Missing, stale, duplicated, hard to find, underused, or wrong format. Low usage is a clue, not a diagnosis.
- Separate exists from used. Test fit, access, discoverability, and use separately. A findable asset may still fail in a live conversation. Check a representative use case before recommending a rewrite; where demand is unverified, investigate before commissioning new content.
- Rate value with visible dimensions. Impact, frequency, strategic alignment. Evidence confidence and effort stay separate. Do not invent weights or divide by effort.
- Assign a decision tier. Mandatory, commit now, validate first, plan, or monitor. High potential with weak evidence is validate first, not build.
- Choose the action. Create, update, consolidate, retire, improve discoverability, or reinforce distribution. Retire only with a successor or an authorized owner, never from low usage alone.
- Sequence within the tier.
Deadline, dependency, effort, owner capacity. Route asset production to
one-pager-and-slide-outline,battlecard-builder, ortalk-track-builder.
What ships with it
3 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.
- 24d ago Changed 5dc549a31a53
- 2mo ago First seen · 73 lines · 66 tokens per session scan A 6f9416e8740d
content-gap-analysis is a skill published in the GitHub repository nthnclrk/enablement-skills (16 stars, last pushed 25d ago), licensed MIT. It adds 66 tokens to every session and 919 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.
content-gap-analysis compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| content-gap-analysisnthnclrk/enablement-skills | Skill | 16 | 25d ago | MIT | A | 66 | Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |