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AC capgo-organization-management

Guides Capgo account lookup and organization administration with the CLI, including `account whoami`, `organization list/add/members/set/delete`, 2FA enforcement, password policy, API-key expiration and hashed-key policy, and apps per organization. Use when listing or creating Capgo organizations, auditing members' 2FA before enforcing it, tightening org security settings, or resolving "Access Denied: Two-Factor Authentication Required" or "Insufficient permissions". Do not use for OTA bundle or channel work (capgo-release-management), native builds (capgo-native-builds), or app-side updater code (capgo-live-updates).

Cap-go/capgo-skills Agent Skills author: Cap-go 2 files body ≈ 1 196 tokens Open the sourcegithub.com↗ analyzed 8 h ago

Guides Capgo account lookup and organization administration with the CLI, including account whoami, organization list/add/members/set/delete, 2FA enforcement…

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

IntegrationAI and agentstype 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
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
93
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

The same skill appears in 1 more place: 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

    • note edit-residue the text marks something as outdated (lines 40): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    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. 10 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. 19 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 1196 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

    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 625: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 19 items
    • +4Has examples (2 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.