agentleFS
Baba01hacker666Baba01hacker666/dummyskills/skills/factual-summarizer/SKILL.md

factual-summarizer

Skill0 starsChanged 2 months agoMITView on GitHub

Summarizes supplied material strictly without adding external claims, assumptions, or hallucinations.

The file

We split this skill into the rules it gives an agent

12 rules. About 0 are common, 8 are distinctive, and 4 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈8

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this skill when:

    line 14
  2. Very specific:

    Do not use to synthesize multi-source research briefs with hypothesis evaluation.

    line 20
  3. Very specific:

    Do not use to verify specific disputed claims.

    line 21
  4. Very specific:

    Do not use to rephrase or polish text.

    line 22
  5. Very specific:

    If source_material is missing: stop and ask: "Please provide the text you would like summarized."

    line 29
  6. Distinctive:

    If the source material does not mention a topic: state "The provided text does not mention this topic." Do not fill gaps from world …

    line 30
  7. Distinctive:

    Follow these numbered actions:

    line 33
  8. Distinctive:

    Write short, clear sentences.

    line 39
  9. Distinctive:

    Check each bullet against source text: if it cannot be pointed to, remove it.

    line 42
  10. Distinctive:

    If the text contains contradictory statements: report both contradictory statements verbatim.

    line 47
  11. Distinctive:

    If the text mentions probabilities or estimates: preserve qualifiers ("approximately", "alleged", "estimated").

    line 48
  12. Distinctive:

    Stop and ask the user when:

    line 80

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Factual Summarizer

Produces strict, grounded summaries of provided text. Every bullet point is backed by exact source sentences with zero external extrapolation.

1. Purpose

Condense long documents, incident reports, or articles into concise facts. "Grounded" means no information outside the supplied text is introduced.

2. When to Use

Use this skill when:

  • Summarizing technical papers, logs, vendor documents, or legal notices.
  • User explicitly requests a factual or neutral summary.
  • Preparing concise input for another model with tight context limits.

3. When Not to Use

  • Do not use to synthesize multi-source research briefs with hypothesis evaluation; use research-brief.
  • Do not use to verify specific disputed claims; use claim-checker.
  • Do not use to rephrase or polish text; use meaning-preserving-editor.

4. Required Inputs

  • source_material: The complete text to summarize (string).
  • max_bullets: Optional maximum number of bullet points (default: 5).

5. Missing-Input Behavior

  1. If source_material is missing: stop and ask: "Please provide the text you would like summarized."
  2. If the source material does not mention a topic: state "The provided text does not mention this topic." Do not fill gaps from world knowledge.

6. Procedure

Follow these numbered actions:

  1. Action 1: Parse Key Statements
    • Extract primary claims, numbers, dates, and conclusions directly stated in the text.
  2. Action 2: Filter Extraneous Commentary
    • Discard rhetorical flourishes, greetings, or off-topic tangents.
  3. Action 3: Formulate Concise Bullets
    • Write short, clear sentences.
    • Restrict count to max_bullets.
  4. Action 4: Verify Grounding
    • Check each bullet against source text: if it cannot be pointed to, remove it.
  5. Action 5: Emit Summary
    • Format using Section 8.

7. Decision Rules

  • If the text contains contradictory statements: report both contradictory statements verbatim; do not reconcile them.
  • If the text mentions probabilities or estimates: preserve qualifiers ("approximately", "alleged", "estimated"); do not convert to certainties.

8. Output Format

Emit the summary using this template:

### Factual Summary

- **Source Word Count**: [Estimated count]
- **Bullet Count**: [Count]

#### Key Factual Findings
- [Fact 1 with specific metrics or entities]
- [Fact 2]
- [Fact 3]

#### Unstated / Excluded Topics
- [Note if a commonly expected detail like dates or cause was omitted in the source]

9. Verification Checklist

  • Every bullet point maps directly to a sentence in the source.
  • No unstated dates, names, or metrics were introduced.
  • Qualifiers (e.g. "likely", "estimated") are preserved.
  • Bullet count does not exceed max_bullets.

10. Common Failures and Recovery

Failure SymptomCauseRecovery Action
Hallucinated backgroundModel drawing on pretraining dataDelete any sentence not verifiable in provided source.
Over-generalizingReplacing specific numbers with "several"Keep exact numbers and metrics from text.

11. Stop or Escalation Conditions

Stop and ask the user when:

  • Source material is in an unreadable format or foreign language not requested.

12. Examples

Example 1: Successful Execution

Input:

Source: The Apollo 11 lunar module Eagle landed on the Moon on July 20, 1969, at 20:17 UTC. Neil Armstrong became the first person to step onto the lunar surface six hours and 39 minutes later on July 21 at 02:56 UTC. Buzz Aldrin joined him 19 minutes later. They spent two hours and 31 minutes exploring the site.
Max bullets: 3

Output:

### Factual Summary

- **Source Word Count**: 62 words
- **Bullet Count**: 3

#### Key Factual Findings
- Apollo 11's lunar module Eagle landed on the Moon on July 20, 1969, at 20:17 UTC.
- Neil Armstrong stepped onto the lunar surface on July 21 at 02:56 UTC, followed 19 minutes later by Buzz Aldrin.
- Armstrong and Aldrin explored the landing site for two hours and 31 minutes.

#### Unstated / Excluded Topics
- Source does not mention the third astronaut (Michael Collins) or launch details.

Example 2: Ambiguous or Missing Input

Input:

Source: "The meeting occurred."

Output:

### Factual Summary

- **Source Word Count**: 3 words
- **Bullet Count**: 1

#### Key Factual Findings
- A meeting occurred.

#### Unstated / Excluded Topics
- Date, time, participants, location, and agenda are all omitted in the source text.

Example 3: Expected Final Output

Output:

### Factual Summary

- **Source Word Count**: 85 words
- **Bullet Count**: 2

#### Key Factual Findings
- System outage began at 14:02 UTC following a configuration reload in the edge gateway.
- Traffic was rerouted to secondary region at 14:18 UTC, restoring availability to 100%.

#### Unstated / Excluded Topics
- Root cause of the edge gateway reload failure is not stated.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.