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CF climate-energy-super-intelligence

Your climate and energy brain trust. 25 named personas across 7 cells covering energy transition, carbon markets, climate modeling, sustainability, grid infrastructure, environmental policy, and ESG.

coco-research/coco Agent Skills author: coco-research 38 files · 1 script body ≈ 582 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Your climate and energy brain trust.

As a process F 34/100 · No process to follow — weak spots: steps, result and completion, when it triggers

ReferenceInfrastructuretype 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
C
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
59
Run on models
none yet
Process rating
F
34/100
No process to follow
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
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: 38. 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")
  • note frontmatter-key unknown frontmatter key "team_id"
  • note frontmatter-key unknown frontmatter key "team_name"
  • note frontmatter-key unknown frontmatter key "last_updated"
  • note frontmatter-key unknown frontmatter key "schema_version"

Process rating: all ten parameters 34/100

  • 0Steps. Prose only: no discrete steps
  • 0Result and completion. Does not say what the result is
  • 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
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (climate-energy-super-intelligence) differs from the folder (climate-energy)
  • 100Tools and files. No external tools needed
  • 100Execution cost. Instruction body is 582 tokens
  • 100Running it twice. No mutating operations

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)
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 199: enough signal without eating the budget
  • +4Structure: 3 headings

Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.