Restate the last technical message in plain human language — no jargon, no shorthand, every fact and number kept. For 'say it plainly' or when a reply was too dense.
v1.0LATEST
NewUpdated Nov 8, 2026
Bro
Say the last message again, plainly.
Rules
Keep every fact and every number; drop every acronym the user has not
used, every codename, and every piece of scaffolding vocabulary.
One thought per sentence. Short sentences win.
Name who or what each actor is the first time ("the test runner — the
program that checks the code") and then use the plain name.
If something in the original was wrong or overstated, say so while
restating; plain language is not a chance to launder a claim.
Length: however many plain sentences the facts need — terseness that
drops content is not plainness.
Files1
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Overall Score
82/100
Grade
B
Good
Grades are signals, not a certification. Always review a skill yourself before use.
Safety
95
Quality
80
Clarity
85
Completeness
72
Summary
Bro is a conversational instruction skill that directs an AI agent to restate technical messages in clear, plain language while preserving all factual content, numbers, and important details. It operates as a read-only instruction set for communication style — no file operations, no shell execution, no side effects.
Detected Capabilities
text analysisinstruction followinglanguage transformation
Trigger Keywords
Phrases that agents use to match this skill to user intent.
simplify technical messageexplain in plain languagerestate plainlydecode jargonclarify dense text
Referenced Domains
External domains referenced in skill content, detected by static analysis.
github.com
Use Cases
Simplify dense technical explanations for non-technical stakeholders
Clarify jargon-heavy error messages into actionable guidance
Make complex API documentation or architecture discussions accessible
Verify technical claims by restating them plainly and checking for accuracy
Transform overly abbreviated or shorthand replies into complete sentences
Quality Notes
Concise and well-structured rules that are clear and actionable
Good emphasis on preserving facts and numbers while dropping jargon — clarifies the difference between simplification and information loss
Practical guidance on naming actors/entities on first mention, which improves clarity
Rule about acknowledging inaccuracy during restatement is thoughtful — prevents misleading simplifications
Skill is appropriately scoped to a single, focused task with no dependencies or side effects
Model: claude-haiku-4-5-20251001Analyzed: Nov 8, 2026
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