Transform technical communication into structured business formats.
This skill transforms dense technical communication into clear, structured business formats using proposition extraction (identify all facts and relationships) and deterministic templates (apply consistent structure). It extracts every detail without loss, categorizes by business relevance, applies a standard template with professional tone, and verifies completeness before delivery.
Core principle: Transformation ≠ creation. Only restructure existing input; always extract from existing input and restructure it for executive clarity with preserved technical accuracy.
| Signal | Load These Files | Why |
|---|---|---|
| example-driven tasks | examples.md | Loads detailed guidance from examples.md. |
| tasks related to this reference |
templates.md |
Loads detailed guidance from templates.md. |
Goal: Extract every proposition from the input before structuring anything. This prevents information loss and ensures technical accuracy is preserved.
Step 1: Classify input type
Identify the communication type (this determines categorization strategy in Phase 2):
Step 2: Extract all propositions
Parse each sentence systematically. Extract all propositions before summarizing — summarizing skips propositions and loses facts:
Step 3: Document implicit context
Surface assumptions the author takes for granted but the audience needs stated. Non-technical audiences cannot act without this:
Step 4: Count and validate propositions
## Parsing Result
Input type: [technical update | debugging narrative | status report | dependency discussion]
Proposition count: [N distinct facts/claims]
Emotional markers: [frustration | satisfaction | urgency | neutral]
Extracted Propositions:
1. [Fact/claim 1]
2. [Fact/claim 2]
... (ALL propositions - NO information loss)
Implicit Context:
- [Assumption 1]
- [Assumption 2]
Gate: ALL propositions extracted with zero information loss. Proceed only when gate passes.
Goal: Categorize and prioritize all extracted propositions by business relevance. This prevents unsolicited sections and keeps output focused on what matters most.
Step 1: Categorize propositions
Organize by type (categorization determines template section placement):
Status: [items with current state]
Actions: [completed, in-progress, planned]
Impacts: [business and technical consequences]
Blockers: [dependencies, constraints]
Next: [required actions]
Step 2: Priority order
Rank by impact to executive decision-making, not completeness:
Only the highest-priority categories go into the output. Lower-priority items are preserved in Technical Details but not emphasized.
Step 3: Identify information gaps
Flag any propositions that need clarification before transformation. Ask for specifics only when severity classification is ambiguous:
Gate: All propositions categorized and prioritized. Proceed only when gate passes.
Goal: Apply standard template with professional tone. This ensures consistent, executive-ready formatting without speculative sections.
Step 1: Apply standard template
Include only the sections in the standard template (Risk Assessment, Historical Context, Mitigation Strategies). Use ONLY this structure:
**STATUS**: [GREEN|YELLOW|RED]
**KEY POINT**: [Single most important business takeaway]
**Summary**:
- [Primary accomplishment/issue]: [Business impact]
- [Current focus/blocker]: [Expected outcome/resolution need]
- [Secondary consideration]: [Implications]
**Technical Details**:
[2-3 sentences maximum preserving technical accuracy]
**Next Steps**:
1. [Specific action with timeline if available]
2. [Secondary action with ownership implications]
3. [Follow-up considerations]
Step 2: Tone adjustment
The transformation rules are deterministic (apply all):
Step 3: Status classification
Apply criteria consistently (inconsistency confuses stakeholders and erodes trust):
Always document reasoning: "Status: YELLOW (deployment successful but monitoring pending)" not just "Status: YELLOW"
Step 4: Action item specificity
Vague action items cannot be executed. Every next step MUST include:
Gate: Output follows template structure with professional tone and all specificity rules applied. Proceed only when gate passes.
Goal: Confirm transformation quality before delivery. All gates must pass; proceed only when complete.
Step 1: Compare output against extracted propositions — NO information loss allowed. If a fact from Phase 1 doesn't appear in output, it belongs in Technical Details.
Step 2: Verify technical accuracy — terms, metrics, causal chains preserved exactly. Preserve exact technical terms ("database issues" for "Redis cluster failover") — specificity is required.
Step 3: Confirm status indicator matches actual severity. Check reasoning against actual criteria (GREEN ≠ YELLOW vs YELLOW ≠ RED boundaries).
Step 4: Validate action items are specific — check each next step for (verb, scope, owner, timeline). "Fix the issue" fails; "Complete Redis failover testing in staging (DevOps, by EOW)" passes.
Step 5: Check appropriate detail level for target audience. If audience is non-technical, Technical Details should bridge jargon with plain explanations without losing precision.
Step 6: Document transformation summary to prove gate passage:
## Transformation Summary
Input type: [type]
Propositions extracted: [N]
Status assigned: [GREEN|YELLOW|RED] ([reasoning])
Information loss: None
Template applied: standard
Gate: All verification checks pass. Transformation is complete. Complete all 6 steps before delivering.
User says: "I fixed the database issue but then the API started failing so I had to rollback and now we're investigating the connection pool settings which might be related to the recent Kubernetes upgrade." Actions:
User says: "I can't make progress because the API team hasn't responded in 3 days and my sprint is at risk" Actions:
User says: "The latest deploy broke checkout completely, users are getting 500 errors, we rolled back but some orders might be lost" Actions:
Cause: Technical terms or acronyms critical to business impact are undefined.
Solution:
Cause: Input contains mixed signals (e.g., issue resolved but monitoring incomplete).
Solution:
Cause: Input contains multiple unrelated topics that could cross-contaminate status classifications.
Solution:
Constraint distribution in error handling:
${CLAUDE_SKILL_DIR}/references/templates.md: Status-specific templates, section formats, phrase transformations${CLAUDE_SKILL_DIR}/references/examples.md: Complete transformation examples with proposition extraction