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BC capacitor-offline-first

Designs and implements offline-first data in Capacitor apps - local SQLite source of truth with @capgo/capacitor-fast-sql (`FastSQL.connect`, `KeyValueStore`), an outbox/sync queue, delta pulls, conflict resolution, @capacitor/network `networkStatusChange`, background sync with @capgo/capacitor-background-task, and why localStorage/IndexedDB get evicted and service workers break plugin injection in native WebViews. Use when the app must work without internet, data disappears after iOS storage pressure, sync duplicates or loses writes, or `Plugin not implemented` appears after adding a service worker. Do not use for migrating an existing SQLite plugin (sqlite-to-fast-sql), shipping web bundle updates offline (capgo-live-updates), HTTP security/certificate pinning (capacitor-security), or general performance (capacitor-performance).

Cap-go/capgo-skills Agent Skills author: Cap-go 4 files body ≈ 1 905 tokens Open the sourcegithub.com↗ analyzed 9 h ago

Designs and implements offline-first data in Capacitor apps - local SQLite source of truth with @capgo/capacitor-fast-sql (FastSQL.connect, KeyValueStore), an…

As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting

ProcedureSoftware 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%
84
Run on models
none yet
Process rating
C
61/100
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: capacitor-offline-first (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: 4. 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 61/100

    • 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
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
    • 100Steps. 35 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 1905 tokens
    • 100Running it twice. Mutating operations check current state

    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
    • +3Description length 842: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -5TODO / placeholder text left in the skill
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 35 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

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