Prepare and evaluate an autonomous agent transaction without self-granting authority or moving money. Use for bounded authority requests, pre-execution checks, payment and delivery evidence, safe retry decisions, outcome verification, and reconciliation.
Prepare a bounded Agoragentic deployment handoff or preview. Use for Agent OS export, deployment-readiness evidence, runtime probes, and owner-approved transition from local proof to hosted operation.
Preview and execute a bounded Agoragentic capability after explicit owner or host approval. Use for task routing, capability matching, execution constraints, and invocation/receipt capture.
Apply Agoragentic local governance before an agent performs side effects. Use for policy checks, approval packets, authority boundaries, and no-spend Harness or ECF preparation.
Connect an external agent host, framework, tool, or specialist engine to Agoragentic governance and receipts. Use for adapters, lifecycle mapping, MCP/tool discovery, and bounded integration design.
Produce or inspect Agoragentic local proof and receipt evidence for an agent run. Use for evidence refs, hashes, run status, policy decisions, approval linkage, and reconciliation.
Prepare an Agoragentic capability for commercial listing or paid routing. Use for listing readiness, pricing/payment metadata checks, seller evidence, and marketplace handoff without publishing or spending automatically.
Route an Agoragentic task to the smallest applicable skill. Use when the request involves Agoragentic execution, governance, transaction assurance, proof/receipts, deployment, selling, or integration and the correct branch is not yet known.
Use Agoragentic from an AI assistant for public discovery, registry and receipt proof, owner-approved registration, authenticated budget inspection, governed task routing, or federation evidence. Always check live market authority before any paid or trust-changing action.
Evidence-first codebase audit for correctness, security, privacy, data, integration, operational, test, and docs-vs-reality risks. Use when the user asks for a Fable-5 audit, exhaustive audit, bug hunt, risk review, codebase audit, security/integration audit, or asks Codex to find issues before changing code.
Fable-5 deep code review for pull requests, branches, diffs, or proposed patches. Use when the user asks for deep review, PR review, branch review, review comments, regression review, or independent verification of a change.
Evidence-grounded design option generation for technical architecture, migrations, APIs, data models, safety controls, operational changes, and implementation plans. Use when the user asks for options, tradeoffs, design review, migration strategy, or a decision memo grounded in the current codebase.
Claim-by-claim verification of docs, status reports, launch claims, changelogs, READMEs, runbooks, and "done/tested/working/live" assertions against source, tests, artifacts, and runtime evidence. Use when the user asks Codex to fact-check, verify claims, audit truthfulness, or compare docs to reality.
Repo-wide implementation workflow for renames, migrations, consistency updates, generated-surface sync, docs/tests updates, and cross-cutting cleanup. Use when the user asks for a Fable-5 sweep, broad rename, consistency pass, migration, or "find every place and update it" task.
Source-grounded codebase understanding for behavior, architecture, boot flow, data flow, integration wiring, or "how does this work" questions. Use when the user asks Codex to explain a system, trace a path, map a subsystem, or answer behavior questions with citations and unknowns.
Prepare or read explicit reviewed evidence-preserving context packs for Codex handoffs. Use when asked to preserve exact evidence across compaction or when a Context Keeper hook points to a staged snapshot. Never scan raw transcripts.
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originalMIT
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