SKILLEMALL.ai

AC ia-reflect

Session retrospective and skill audit. Use when asked to reflect, do a retrospective, review lessons learned, audit what went well or wrong, or review session effectiveness.

ClawHub Agent Skills author: Ilia Alshanetsky v4.5.2 MIT-0 3 files body ≈ 2 042 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

AnalyzerOperations and projectsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
C
55/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
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 "class"

    Process rating: all ten parameters 55/100

    • 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
    • 40Result and completion. Does not say what the result is
    • 40Consistency. Frontmatter name (ia-reflect) differs from the folder (compound-eng-reflect)
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70Failures and branches. 9 branches
    • 100Steps. 19 steps
    • 100Execution cost. Instruction body is 2042 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
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 173: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 19 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

    External checks

    ClawHub: clean
    This skill is a session-retrospective helper that may propose memory or skill edits, but it consistently requires user authorization before writing anything.
    LLM: benign (high) · VirusTotal: · 8 Sept 2026