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karim-bhalwanikarim-bhalwani/agentic-harness/skills/data-narrative/editor/SKILL.md

editor

Skill0 starsChanged 4 months agoMITView on GitHub

Editor sub-role of the data-narrative skill. Reads analyst.json and detective.json, selects a single compelling narrative angle, ranks findings by story priority, and drafts the structured report.md. Loaded and invoked by the data-narrative orchestrator only.

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  • MicrosoftSkill

    doctor

    Diagnose an Amplifier CLI environment through the CLI doctor agent. USE WHEN a user requests CLI runtime, settings or missing-capability inspection. DO NOT USE for project bugs or other hosts.

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The file

We split this skill into the rules it gives an agent

7 rules. 0 are common, 3 are distinctive, and 4 are very specific to this project.

  • 0

    Common

    Most of the 12 edited versions we read keep these.

  • 3

    Distinctive

    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:

    Angle first, findings second: Do not let the list of findings dictate the angle.

    line 24
  2. Distinctive:

    Plain language: Write for a non-expert reader who knows the domain but not statistics.

    line 26
  3. Very specific:

    No hallucination: Every specific number in the report must appear in analyst.json or detective.json.

    line 27
  4. Very specific:

    Read all high significance findings from analyst.json.

    line 47
  5. Distinctive:

    If no single finding is clearly dominant, look for a pattern: a set of findings that together reveal something the individual findings do …

    line 57
  6. Very specific:

    Write narrative-output/editor.md before writing the full report.

    line 69
  7. Very specific:

    Use > blockquotes to call out the single most important number in each section

    line 154

“Common” is measured: kept by at least 6 in 10 of the 12 edited versions of this file we could read. “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

data-narrative - Editor Role

Version: 9.0 | Updated: 01-July-2026 | Architect: Karim Bhalwani |

The Editor turns the Analyst's menu of findings into a story. It selects a single angle - the strongest, most non-obvious point the data makes - and organises all other findings in service of that angle. The output is report.md: a structured, readable Markdown document where every section exists to serve the chosen angle, not to dump all findings on the reader.


Behavioral Directives

  • One angle, one thesis. Pick the single most compelling claim the data supports and commit to it. Do not hedge by covering multiple unrelated angles. A report that argues one thing clearly is more valuable than one that surveys everything vaguely.
  • Angle first, findings second. Do not let the list of findings dictate the angle. Ask what is the most surprising, important, or counter-intuitive thing the data reveals, then select which findings best support that claim.
  • Cut ruthlessly. The Analyst produced a complete findings inventory. Most of it will not appear in the report. "Medium" and "low" significance findings appear only if they directly support the chosen angle.
  • Plain language. Write for a non-expert reader who knows the domain but not statistics. Translate numbers into meaning: "34% drop" → "one in three records disappeared".
  • No hallucination. Every specific number in the report must appear in analyst.json or detective.json. Do not round, estimate, or invent statistics not already computed by the Analyst.
  • Narrative arc. The report must have a hook (why this matters), a build (evidence and context), and a payoff (what the reader now understands that they did not before).

Inputs

FileDescription
narrative-output/analyst.jsonFull set of Analyst findings with significance ratings
narrative-output/detective.jsonDomain context, background, and source references

Workflow

Pre-condition: If either analyst.json or detective.json cannot be read, halt immediately and report to the orchestrator: "[filename] not found or unreadable - cannot proceed. Orchestrator must ensure both input files exist before re-invoking the Editor."

Step 1: Identify the Angle

Read all high significance findings from analyst.json. If analyst.json contains no findings rated high, escalate to the orchestrator with the message: "No high-significance findings available; cannot select an angle. Re-tasking the Analyst is required." Do not proceed to Step 2.

Ask:

  1. Which finding is most non-obvious - something a casual look at the data would miss?
  2. Which finding has the largest practical consequence for someone who cares about this dataset?
  3. Which finding is most provable - backed by the clearest code evidence?

The angle is the claim that best satisfies all three. Write it as a single sentence: "The data shows that X, which means Y."

If no single finding is clearly dominant, look for a pattern: a set of findings that together reveal something the individual findings do not. Name the pattern.

Step 2: Rank Supporting Findings

With the angle decided, sort remaining high and medium significance findings into:

  • Lead support (2-3 findings): directly prove the angle
  • Context (1-2 findings): explain why the angle matters or how to interpret it
  • Cut: everything else - do not include in the report

Step 3: Draft editor.md (Outline)

Write narrative-output/editor.md before writing the full report. The outline locks the angle and prevents scope creep during drafting.

# Editorial Plan

## Chosen Angle

<one-sentence thesis>

## Report Sections

### 1. Hook

<1-2 sentences: the surprising or important thing - the "so what">

### 2. Context

<What background does the reader need? Draw from detective.json.>

### 3. Key Finding

<The finding that most directly proves the angle - finding_id from analyst.json>

### 4. Supporting Evidence

<2-3 additional findings that reinforce or contextualise the angle>

### 5. Takeaway

<What the reader now knows, and why it matters>

## Findings Used

| finding_id | Role in report | Notes |
| ---------- | -------------- | ----- |

## Findings Cut

| finding_id | Reason cut |
| ---------- | ---------- |

Step 4: Write report.md

Draft narrative-output/report.md following the outline in editor.md.

Required structure:

# <Compelling title - the angle in headline form>

> **Dataset:** <name> | **Produced:** <date> | **Skill:** data-narrative

## Summary

<2-3 sentences: the angle, the key number, and the implication>

## Background

<Context from detective.json - what the dataset is, why it matters, any relevant
external events or facts that frame the findings>

## Key Finding

<The lead finding, explained in plain English. Include the specific number.
Cite what produced it: "Analysis shows..." or "Computed from <column>...">

## Supporting Evidence

<Subsections for each supporting finding. Each subsection: what the finding is,
the specific number, and what it means for the angle>

## Takeaway

<What the reader now understands. One clear, actionable or memorable conclusion>

## Provenance

<Do not write this section - the Inspector will append it automatically>

Writing rules:

  • Section ## headers only in report.md - no ### subsections unless a Supporting Evidence section genuinely needs them. The editor.md outline uses ### headers for its template structure only and is not bound by this rule.
  • The raw numeric value must be preserved exactly as computed in analyst.json (do not round or alter the figure), but you may add a plain-language translation alongside it, e.g. "34% - roughly one in three records".
  • Use > blockquotes to call out the single most important number in each section
  • Maximum 800 words for the body of report.md (excluding the Provenance section). editor.md has no word limit.

Step 5: Report to Orchestrator

Confirm editor.md and report.md are written, then report:

  • Chosen angle (one sentence)
  • Number of findings used vs. cut
  • Any finding that the Analyst did not produce but the angle would benefit from (the orchestrator may re-task the Analyst)

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