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 TrueClicks/claude-plugins --skill skill-060-in-market-custom-intent-layeringgit clone --depth 1 https://github.com/TrueClicks/claude-pluginsWrote 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/trueclicks/claude-plugins/skill-060-in-market-custom-intent-layering)<a href="https://agentmods.dev/skills/trueclicks/claude-plugins/skill-060-in-market-custom-intent-layering"><img src="https://agentmods.dev/badge/skills/trueclicks/claude-plugins/skill-060-in-market-custom-intent-layering/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/trueclicks/claude-plugins/skill-060-in-market-custom-intent-layering"><img src="https://agentmods.dev/badge/skills/trueclicks/claude-plugins/skill-060-in-market-custom-intent-layering.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 | $0.00026 | $0.00744 |
| Opus 5.5 | $0.00010 | $0.00298 |
| Sonnet 5.5 | $0.00005 | $0.00149 |
| Haiku 4.5 | $0.00003 | $0.00074 |
Grade A, and why
skill-060-in-market-custom-intent-layering 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 21d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill 060: In-Market and Custom Intent Audience Layering
Purpose
In-market segments and custom intent audiences help reach users with demonstrated purchase intent. This skill evaluates current usage, identifies performance patterns, and recommends additional segments to add or custom intent audiences to create.
Data Requirements
Data Source: Custom GAQL Required
The standard export includes audience targeting setup but not audience-level performance metrics.
Standard Data:
data/account/campaigns/*/audience_targeting.md- Current audience setup
GAQL Query:
SELECT
campaign.name,
ad_group.name,
ad_group_criterion.user_interest.user_interest_category,
ad_group_criterion.custom_intent.custom_intent,
ad_group_criterion.bid_modifier,
metrics.impressions,
metrics.clicks,
metrics.cost_micros,
metrics.conversions,
metrics.conversions_value
FROM ad_group_audience_view
WHERE segments.date DURING LAST_30_DAYS
AND metrics.impressions > 0
Run via /google-ads:get-custom with query name audience_performance.
Analysis Steps
-
Review current audience setup: Read audience targeting files, identify in-market audiences in use, identify custom intent audiences, note targeting mode.
-
Evaluate in-market audience performance: Fetch performance data, calculate CPA/ROAS vs non-audience traffic, identify high and low performers.
-
Identify missing opportunities: Relevant in-market segments not used, custom intent audiences not created, high-performing audiences underutilized.
-
Generate recommendations: In-market segments to add, custom intent audiences to create, bid adjustments for existing audiences.
Thresholds
| Condition | Severity |
|---|---|
| No in-market or custom intent audiences used | High |
| In-market audience CPA >30% below average | High (increase bid) |
| In-market audience CPA >50% above average | Warning (decrease/remove) |
| Missing relevant in-market category for business | Warning |
| Custom intent audience not created for competitors | Info |
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.
- 21d ago First seen · 92 lines · 26 tokens per session scan A f1a916c8a000
skill-060-in-market-custom-intent-layering is a skill published in the GitHub repository TrueClicks/claude-plugins (2 stars, last pushed 22d ago), licensed MIT. It adds 26 tokens to every session and 744 once invoked, about $0.0001 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 2026-10-08.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…