agentsclimarketplace

Agent readiness

Skill JKHeadley/instar/skills/agent-readiness

Persistent Claude Code agents with scheduling, sessions, memory, and Telegram.

Install
npx -y skills add JKHeadley/instar --skill agent-readiness

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its author says it does

Copied from the file, not written here

Score a task or workflow on its coordination-vs-judgment ratio to tell whether it's a good agent candidate (EXO 3.0 task-decomposition matrix).

SKILL.md

2.2 KB, as published. Nobody here has run it

/agent-readiness

Salim Ismail's EXO 3.0 diagnostic, made runnable: score a piece of work on its coordination-vs-judgment ratio. Coordination work — routing information, approvals, scheduling, status tracking, prescriptive/standardized steps — is what AI agents do best, so it's agent-ready. Judgment work — resolving ambiguity, handling exceptions, navigating relationships, making a call with no playbook — should stay with (or escalate to) humans.

When to use

  • Before delegating a task/workflow to an agent — is it actually a good candidate?
  • When deciding whether a process should be fully automated, agent-with-oversight, hybrid, or kept human-led.
  • When mapping which of your workflows a small team + agents could rebuild first (Salim: "every task that scores high on coordination has agent readiness").

How

Score a task:

curl -X POST -H "Authorization: Bearer $AUTH" -H 'Content-Type: application/json' \
  -d '{"task":{"name":"Invoice intake","description":"Route invoices, schedule approvals, track status, compile a weekly report, notify owners."}}' \
  http://localhost:${INSTAR_PORT:-4042}/agent-readiness/score

Score a workflow (by its steps):

curl -X POST -H "Authorization: Bearer $AUTH" -H 'Content-Type: application/json' \
  -d '{"workflow":{"steps":["Fetch the record","Assign accounts","Schedule orientation","Update the tracker"]}}' \
  http://localhost:${INSTAR_PORT:-4042}/agent-readiness/score

Returns:

{
  "coordinationSignals": 5, "judgmentSignals": 0,
  "coordinationRatio": 1.0, "overallReadiness": 100,
  "recommendation": "deploy-agent",
  "reason": "...",
  "matched": { "coordination": ["route","schedule",...], "judgment": [] }
}

recommendation is one of: deploy-agent (75+), agent-with-oversight (55–74), hybrid (40–54), human-led (<40). Deterministic + advisory — it answers a question; it never blocks. Pair it with the MTP Protocol (/intent/org/test-action) to check both "is this agent-ready?" and "does our purpose endorse it?"

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.