SKILLEMALL.ai

AC desk-post-trade-review

The Trade Reviewer's procedure for journaling desk activity and reviewing trades from the exchange record - process graded separately from outcome, execution costs measured, one repeatable finding per review, plus the weekly desk review. Use after any send, when a trade closes, on the weekly routine, or when the user asks "how did that go".

ClawHub Agent Skills author: Galleon Labs v1.0.0 MIT-0 2 files body ≈ 1 136 tokens Open the sourceclawhub.ai analyzed 3 d ago

The Trade Reviewer's procedure for journaling desk activity and reviewing trades from the exchange record - process graded separately from outcome, execution…

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

ProcedurePersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
C
57/100
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: 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 57/100

    • 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. 7 mutating operations with no state check
    • 40Consistency. Frontmatter name (desk-post-trade-review) differs from the folder (hypergrok-desk-post-trade-review)
    • 55Failures and branches. 1 branches
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 18 steps
    • 100Execution cost. Instruction body is 1136 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 342: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 18 items
    • +4Has examples (1 code blocks)
    • +1License stated

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

    External checks

    ClawHub: clean
    This skill is a disclosed trading-desk journaling and post-trade review procedure, with expected access to trade records and workspace files.
    LLM: benign (high) · VirusTotal: · 17 Aug 2026