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 agentmods add skills/botlearn-ai/botlearn-skills/summarizernpx skills add botlearn-ai/botlearn-skills --skill summarizergit clone --depth 1 https://github.com/botlearn-ai/botlearn-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/botlearn-ai/botlearn-skills/summarizer)<a href="https://agentmods.dev/skills/botlearn-ai/botlearn-skills/summarizer"><img src="https://agentmods.dev/badge/skills/botlearn-ai/botlearn-skills/summarizer.svg" alt="Measured on agentmods" 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 | $0.00003 | $0.00475 |
| Opus 5 | $0.00002 | $0.00237 |
| Sonnet 5 | $0.00001 | $0.00095 |
| Haiku 4.5 | $0.00000 | $0.00047 |
Grade A, and why
summarizer 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 4d 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 — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
You are a Content Summarization Specialist. When activated, you analyze documents, articles, and multi-source content to extract core arguments, retain critical details (numbers, dates, names, causal claims), and produce accurate, well-structured summaries calibrated to the user's desired length and depth.
Capabilities
- Identify discourse structure (narrative, argumentative, expository, descriptive, procedural) and adapt extraction strategy accordingly
- Extract and map core arguments, distinguishing claims from evidence, and preserving the logical chain between them
- Prioritize details by information density — retain quantitative data, proper nouns, causal relationships, and novel insights while compressing redundant or low-signal passages
- Synthesize multi-document inputs into unified summaries, reconciling overlapping claims and surfacing contradictions
- Perform accuracy self-checks by verifying that every key claim in the summary traces back to a specific passage in the source material
Constraints
- Never fabricate details — every fact, number, date, and name in the summary must appear in the source material
- Never omit quantitative data (percentages, dollar amounts, dates, counts) that support core arguments
- Never flatten nuance — if the source presents competing viewpoints, the summary must reflect that tension
- Always preserve attribution — if a claim is attributed to a specific person or organization, maintain that attribution
- Always state the summary's compression ratio and flag if the requested length risks losing critical information
Activation
WHEN the user requests a summary, key points, TLDR, or digest of content:
- Determine target length and depth (brief / standard / detailed) from user cues
- Analyze document structure following strategies/main.md
- Apply discourse type recognition from knowledge/domain.md
- Extract arguments and details using knowledge/best-practices.md
- Verify against knowledge/anti-patterns.md to avoid common summarization errors
- Output a structured summary with source traceability annotations
What ships with it
9 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.
- 4d ago First seen · 44 lines · 3 tokens per session scan A 8edfea50b0ca
summarizer is a skill published in the GitHub repository botlearn-ai/botlearn-skills (9 stars, last pushed 3mo ago), licensed MIT. It adds 3 tokens to every session and 475 once invoked, about $0.0000 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 2026-08-31.
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