SKILLEMALL.ai

AD orca

Launch and coordinate agent sessions inside the Orca IDE runtime (stablyai/orca). Topics: send - find a running Orca terminal by title/preview/worktree and deliver a prompt to it, always disambiguating with a question when more than one candidate matches and never targeting the caller's own pane [send.md]. launch - start a new agent session (claude, antigravity, openclaw, codex, and 30+ other supported agents) in a fresh or existing worktree [launch.md]. install - install the stablyai/orca skill bundle into Claude Code, OpenClaw, or Antigravity, asking whether to ghq-clone + symlink or use a plain marketplace install [install.md]. Use when: "send this to the claude session working on X", "hand this off to another agent in Orca", "spawn a new codex/antigravity worktree", "which Orca terminal is running Y", "install the orca skills into openclaw/antigravity", "Orca worktree", "Orca terminal send".

ClawHub Agent Skills author: es6kr v0.2.1 MIT-0 11 files · 4 scripts body ≈ 942 tokens Open the sourceclawhub.ai analyzed 3 d ago

Launch and coordinate agent sessions inside the Orca IDE runtime (stablyai/orca).

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
D
43/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 11. 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 43/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 11 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 100Steps. 6 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 942 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 908: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -32 of 2 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 6 items
    • +4Has examples (3 code blocks)
    • +1License stated

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

    External checks

    ClawHub: suspicious
    The skill is mostly coherent for Orca session management, but it includes persistent cross-harness plugin installation guidance and mutable symlink installs that users should review before trusting.
    LLM: suspicious (high) · VirusTotal: · 10 Sept 2026