SKILLEMALL.ai

AC capgo-release-workflows

Designs repository-owned release pipelines for Capacitor apps that combine Capgo live updates, native builds (Capgo Build or the team's own CI runners), and App Store / Play publishing, with an automatic OTA-vs-native gate (`bundle releaseType`, `build needed`), staged channels, and rollback. Use when the user wants one release system covering OTA, builds, and store publishing, is replacing a hosted release service with CI they own, or asks how CI should decide between a live update and a store build. Do not use for single-step tasks (capgo-release-management, capgo-native-builds, capgo-live-updates), non-Capacitor apps, or Ionic Enterprise plugin migration (ionic-enterprise-sdk-migration).

Cap-go/capgo-skills Agent Skills author: Cap-go 2 files body ≈ 1 392 tokens Open the sourcegithub.com↗ analyzed 9 h ago

Designs repository-owned release pipelines for Capacitor apps that combine Capgo live updates, native builds (Capgo Build or the team's own CI runners), and…

As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureGitHubInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
58/100
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
This is a copy of a skill from another catalog; the rating counts the canonical one: capgo-release-workflows (Cap-go/capgo-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 58/100

    • 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. 4 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 100Steps. 34 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 1392 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
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 699: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 34 items
    • +4Has examples (2 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.