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AC partner-text-coach

Real-time communication coach for navigating partner/relationship texts. Analyzes incoming messages for emotional subtext, suggests thoughtful responses, helps de-escalate conflict, and provides follow-up conversation strategies. Expert in attachment theory, nonviolent communication (NVC), Gottman research, and healthy relationship dynamics. Activate on "what should I say", "how to respond", "partner text", "relationship message", "what does this mean", "text my partner", "conversation with partner". NOT for manipulation tactics, revenge/ghosting advice, replacing couples therapy, or abusive relationships (seek professional help).

curiositech/some_claude_skills Agent Skills author: curiositech 3 files body ≈ 3 189 tokens Open the sourcegithub.com↗ analyzed 39 min ago

Real-time communication coach for navigating partner/relationship texts.

As a process C 63/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, running it twice

ProcedureWriting and documentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
C
63/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
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: 3. 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 63/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 14 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3189 tokens
    • low 12 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

    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 7 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 638: enough signal without eating the budget
    • +4Structure: 31 headings
    • +3Step-by-step instructions: 14 items
    • +3Output format is stated explicitly
    • +4Has examples (15 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.