SKILLEMALL.ai
GitHub ↗ RU Sign in

BB work-circleback-action-items

Work the action items Circleback captured — find what is assigned to this user, do the ones the workspace can do, and update status only for work that is actually finished. Use when the user asks what they owe, "do my action items", "what's still open from", or wants to close, reassign, or add an action item.

superset-sh/superset Claude Code author: superset-sh NOASSERTION 1 file body ≈ 537 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Work the action items Circleback captured — find what is assigned to this user, do the ones the workspace can do, and update status only for work that is…

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

ProcedureData and analyticstype 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
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
B
66/100
Nearly there
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: 1. 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

    • 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. 1 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 8 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 537 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 310: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 8 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.