SKILLEMALL.ai

AB communication-playbook

World-Class Communication Playbook for HeySalad. Use this skill whenever any communication task is involved — internal team messages, external emails to investors/regulators/partners/customers, presentation structuring, written docs, cross-functional project coordination, meeting facilitation, transparency decisions, or active listening coaching. Trigger for ANY of the following: drafting or reviewing emails, Slack messages, investor updates, regulatory correspondence, pitch decks, slide structure, meeting agendas or notes, RACI matrices, project kickoff docs, 1-on-1 frameworks, feedback conversations, conflict resolution, documentation standards, or communication culture advice. Also trigger when the user asks about tone, channel selection, async comms, BLUF, Pyramid Principle, meeting cadence, psychological safety, or transparency norms. If it involves how HeySalad communicates — internally or externally — use this skill. When in doubt, use it.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 2 files body ≈ 4 341 tokens Open the sourcegithub.com analyzed 2 d ago

World-Class Communication Playbook for HeySalad.

As a process B 66/100 · Nearly there — weak spots: result and completion, failures and branches, running it twice

ProcedureSlackWriting and documentsMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
B
66/100
Nearly there
Result and completion w 14
0
Failures and branches w 10
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 66/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 30Running it twice. 9 mutating operations with no state check
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Execution cost. Instruction body is 4341 tokens
    • 85Steps. 118 steps, 3 vague phrases
    • 100Tools and files. No external tools needed
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 11 top-level sections: this looks like several domains in one skill

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 960: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Structure: 55 headings
    • +3Step-by-step instructions: 118 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.