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BB deliverable-intake

Turns raw captures, dictated braindumps in a deliverable’s inbox/, or recent macwhspr dictation-log entries into proposed planning-wiki changes, shown as a unified diff for author acceptance or rejection. Classifies every capture line as a decision, evidence claim, question, task, or dropped item with a reason, and traces it to its source. Uncertain names and citations remain UNRESOLVED. Applies decisions only with explicit assent. Use when the user says "intake", "absorb my notes", "process the inbox", "I dictated something", or after notes from a talk, meeting, or reading session. Never edits source files, only planning/ and open questions.

scdenney/open-science-skills Claude Code author: scdenney NOASSERTION 2 files body ≈ 1 124 tokens Open the sourcegithub.com↗ analyzed 4 d ago

Turns raw captures, dictated braindumps in a deliverable’s inbox/, or recent macwhspr dictation-log entries into proposed planning-wiki changes, shown as a…

As a process B 75/100 · Nearly there — weak spots: failures and branches, running it twice

ProcedureData and analyticsResearchSoftware developmenttype 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
75/100
Nearly there
Failures and branches w 10
0
Running it twice w 4
30
Result and completion w 14
60
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: open-science-skills

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 75/100

    • 0Failures and branches. Linear process with no failure handling
    • 30Running it twice. 6 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 6 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1124 tokens
    • 100Progress reporting. Reports progress

    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 4 example trigger phrases
    • +3Description length 650: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 6 items

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