SKILLEMALL.ai

AC kokochat-deeply-research

Deep-research course generator for the KokoChat Deeply mini-app. Phase A side of a two-phase pipeline: use the `kokochat-search` skill plus `web_fetch` to collect real sources, narrate the research in Chinese prose, and emit one `koko.deeply.research.notes` fenced block with synthesis + a flat sources list. Phase B runs as a separate stateless inference and turns those notes into the course outline. Fires when the user message looks like '请围绕「<topic>」做一份深度调研课程'.

ClawHub Agent Skills author: Komako v0.5.0 MIT-0 3 files body ≈ 1 529 tokens Open the sourceclawhub.ai analyzed 31 h ago

Deep-research course generator for the KokoChat Deeply mini-app.

As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorResearchtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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

    • note frontmatter-key unknown frontmatter key "triggers"

    Process rating: all ten parameters 54/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 12 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1529 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)
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +3Description length 466: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 12 items
    • +4Has examples (1 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This is a prompt-only KokoChat research helper that uses disclosed web search and page fetching to prepare course notes.
    LLM: benign (high) · VirusTotal: · 28 May 2026