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 FlorianBruniaux/claude-code-plugins --skill stage-3-conceptsgit clone --depth 1 https://github.com/FlorianBruniaux/claude-code-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/florianbruniaux/claude-code-plugins/stage-3-concepts)<a href="https://agentmods.dev/skills/florianbruniaux/claude-code-plugins/stage-3-concepts"><img src="https://agentmods.dev/badge/skills/florianbruniaux/claude-code-plugins/stage-3-concepts/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/florianbruniaux/claude-code-plugins/stage-3-concepts"><img src="https://agentmods.dev/badge/skills/florianbruniaux/claude-code-plugins/stage-3-concepts.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00064 | $0.01324 |
| Opus 5.5 | $0.00026 | $0.00530 |
| Sonnet 5.5 | $0.00013 | $0.00265 |
| Haiku 4.5 | $0.00006 | $0.00132 |
Grade A, and why
talk-stage3-concepts 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 1mo 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Talk Stage 3: Concepts
Builds an exhaustive catalogue of all identifiable concepts in the source material. Each concept is numbered, categorized, and scored for its talk potential.
When to Use This Skill
- After Stage 1 (and Stage 2 if REX mode)
- Before Stage 4 (Position needs the concept catalogue)
- When you want a structured inventory of what's available before choosing an angle
What This Skill Does
- Reads the summary: loads
{slug}-summary.md - Reads the timeline (if available): enriches scoring with verified dates
- Extracts concepts: full scan of the source material
- Categorizes: assigns each concept to a domain category
- Scores: HIGH / MEDIUM / LOW for talk potential
- Optional repo enrichment: if repo_path is provided, analyzes AI config concepts
- Writes output files
Input
talks/{YYYY}-{slug}-summary.md(required)talks/{YYYY}-{slug}-timeline.md(optional, enriches REX concepts)repo_path(optional, for config/infrastructure concept extraction)
Output
talks/{YYYY}-{slug}-concepts.md(main catalogue)talks/{YYYY}-{slug}-concepts-enriched.md(if repo_path provided)
Scoring Criteria
HIGH: Strong potential
- Demonstrable live or with a screenshot
- Counter-intuitive or surprising (triggers a reaction)
- Associated with verifiable numbers
- Concrete and actionable (explainable in 30 seconds)
- Differentiator vs other talks on the same topic
MEDIUM: Moderate potential
- Useful but expected (not surprising)
- Missing concrete proof or numbers
- Too specific to one particular context
- Needs too much explanation for a 30-min talk
LOW: Weak potential
- Too abstract or philosophical without concrete grounding
- Already heavily covered by other speakers
- Requires specific technical background
- Hard to illustrate in a slide
Scoring discipline: Max 30% HIGH. If everything is HIGH, nothing is.
Standard Categories
| Category | Description |
|---|---|
| Architecture | Technical decisions, stack, structural patterns |
| Tooling | Tools, workflows, automations |
| Philosophy | Principles, mindsets, approaches |
| Workflow | Work processes, habits |
| Knowledge Transfer | Onboarding, team, knowledge sharing |
| Problems | Obstacles encountered, trade-offs |
| Open Source | Contributions, sharing, community |
| AI Config | AI configuration, profiles, knowledge feeding |
| AI Infrastructure | Agents, skills, hooks, commands |
| AI Quality | Review, tests, anti-patterns |
| AI Security | Security hooks, guardrails |
| Optimization | Performance, cost/token reduction |
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.
- 1mo ago First seen · 160 lines · 64 tokens per session scan A 4f2b04bdb298
talk-stage3-concepts is a skill published in the GitHub repository FlorianBruniaux/claude-code-plugins (43 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 1,324 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.
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