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 flonat/flonat-research --skill insights-deckgit clone --depth 1 https://github.com/flonat/flonat-researchWrote 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/flonat/flonat-research/insights-deck)<a href="https://agentmods.dev/skills/flonat/flonat-research/insights-deck"><img src="https://agentmods.dev/badge/skills/flonat/flonat-research/insights-deck/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/flonat/flonat-research/insights-deck"><img src="https://agentmods.dev/badge/skills/flonat/flonat-research/insights-deck.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 | $0.00054 | $0.01401 |
| Opus 5 | $0.00027 | $0.00700 |
| Sonnet 5 | $0.00011 | $0.00280 |
| Haiku 4.5 | $0.00005 | $0.00140 |
Grade A, and why
insights-deck 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 7d 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Insights Deck Skill
Archive a Claude Code insights HTML export and generate a Beamer presentation summarising the findings. All outputs go to
log/insights/with date stamps.
When to Use
- After exporting the built-in Claude Code insights report
- When you want a shareable deck summarising how you use Claude Code
- For periodic self-reflection on AI-assisted workflow
Scope
This skill produces two outputs only: an archived HTML report and a Beamer deck. Do NOT use insights suggestions to create plans, rules, CLAUDE.md edits, or other follow-up actions during this skill's execution. If the user wants to act on suggestions, that happens after the deck is delivered — as a separate conversation.
Phase 1 — Generate & Archive Insights
Step 1: Obtain the exported HTML
The insights export is produced by a built-in Claude Code command and cannot be generated by Codex. If no HTML path was provided, tell the user:
Please export the Claude Code insights report, then provide the generated HTML path. I can build the archive and deck from either client.
If an HTML path was supplied, continue directly. Do not require the active client itself to be Claude Code.
Step 2: Locate the generated HTML
After the export completes, find the most recent insights HTML file:
ls -t /tmp/claude-insights-*.html 2>/dev/null | head -1
If not found in /tmp/, check the user's home directory and common download locations. Ask the user for the path if it can't be located automatically.
Step 3: Archive the HTML
Each insights run gets its own date folder:
mkdir -p log/insights/YYYY-MM-DD
cp <source-html> log/insights/YYYY-MM-DD/insights-YYYY-MM-DD-log.html
Use today's date for the timestamp.
Phase 2 — Build Beamer Deck
Step 1: Read and extract findings
Read the archived HTML file (log/insights/YYYY-MM-DD/insights-YYYY-MM-DD-log.html). Extract:
- Usage patterns — most-used tools, session frequency, typical session length
- Strengths — what's working well in the workflow
- Friction points — repeated failures, slow patterns, underused features
- Recommendations — suggested improvements
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.
- 7d ago First seen · 151 lines · 54 tokens per session scan A 1aab594738a6
insights-deck is a skill published in the GitHub repository flonat/flonat-research (133 stars, last pushed 16d ago), licensed MIT. It adds 54 tokens to every session and 1,401 once invoked, about $0.0003 per session on Opus 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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