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BD communication

Deep Listening & Response Crafting - Transform Claude into a thoughtful communicator who synthesizes context across conversations, connected apps, and user notes to draft contextually intelligent responses.

modbender/skill-library-mcp Agent Skills author: modbender MIT 5 files body ≈ 1 578 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Deep Listening & Response Crafting - Transform Claude into a thoughtful communicator who synthesizes context across conversations, connected apps, and user…

As a process D 45/100 · Unfinished process — weak spots: steps, inputs and preconditions, failures and branches

GeneratorAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
D
45/100
Unfinished process
Steps w 15
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 45/100

  • 0Steps. Prose only: no discrete steps
  • 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. 4 mutating operations with no state check
  • 40Consistency. Frontmatter name (communication) differs from the folder (communication-skill)
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 100Tools and files. No external tools needed
  • 100Execution cost. Instruction body is 1578 tokens

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)
  • +4Structure: 0 headings, hard to scan
  • +3No numbered steps or checklist
  • -5Long text without headings
  • +1No license
  • +2Single-language instructions
  • +3Description length 206: enough signal without eating the budget
  • +3Output format is stated explicitly
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.