Imported from chankov/agent-fleet (.versions/0.0.9/skills/orchestration-verification/SKILL.md). Install upstream with npx skills add chankov/agent-fleet --skill orchestration-verification. Copyright stays with the author.

Orchestration Verification — the Verification Contract

Overview

Multi-agent runs drop clearly stated requirements silently. The dispatcher relays the requirement as prose, specialists return prose summaries ("approved", "verification passed"), and the feature ships broken anyway. Propagation is rarely the problem — the requirement is usually right there in the dispatch text. Verification is the problem: nothing exercised the requirement and refused "done" until it passed.

This skill defines the four artifacts that replace prose-as-truth with checkable assertions and named evidence. It is the single canonical source for their formats — orchestrator and specialist personas reference this skill by name instead of restating the schema.

1. Acceptance assertions — the dispatcher converts the request into numbered, individually checkable statements before any builder runs.
2. Parity / touchpoint inventory — for "make X behave like existing Y", an exhaustive list of every site where the exemplar is special-cased; each becomes an assertion.
3. Structured upward return — specialists report assertion status with evidence, never a prose verdict.
4. Requirement-regression reset — on "it's wrong again", stale summaries are invalidated and the assertion set rebuilt from the latest correction before re-dispatch.

When to Use

• Orchestrating specialists through a dispatcher (e.g. the agent-hub harness) on anything beyond a trivial single read.
• A "make X behave like existing Y" request — the parity failure (exemplar implemented, siblings missed) is the dominant multi-agent defect this skill targets.
• UI / visibility / placement work, where a static review can approve a runtime that is actually broken.
• A requirement that has already shipped wrong once — trigger the regression reset before dispatching again.

When NOT to use: single-agent trivial changes, pure reconnaissance, or conversational tasks with no implementation.

Process

The dispatcher runs this loop; the four artifacts below define the formats each step uses.

1. Build the acceptance assertions first (Artifact 1). Before any builder is dispatched, convert the request into a numbered, tagged list of checkable pass conditions. No dispatch goes out before the assertions exist.
2. If the request is "make X behave like existing Y", run the parity inventory first (Artifact 2). Commission a deep-researcher pass that enumerates every site where the exemplar is special-cased, and turn each site into an assertion covering the whole set.
3. Dispatch in vertical micro-slices, assertions passed verbatim. Each dispatch carries the relevant assertions word-for-word — never a paraphrase — and ends at a named gate.
4. Accept only structured returns (Artifact 3). Specialists report assertion status with named evidence, not a prose verdict. Demote any "proven" claim without evidence to unproven.
5. Gate each slice on proven assertions. Advance only on assertions that came back proven; unproven and failed both mean not done and feed the next dispatch. A runtime-ui assertion is closed only by an actual runtime observation, never a static review.
6. On "wrong again", run the regression reset (Artifact 4). Invalidate stale summaries, rebuild the affected assertions from the latest correction (re-running the parity inventory for "behave like" cases), then re-dispatch.
7. Recover the ledger after compaction. If the running context is summarized, re-read the full assertion text and evidence (e.g. get_assertions in the agent-hub harness) before re-dispatching or reporting done — a counts-only status line is not enough to gate on.

Artifact 1 — Acceptance assertions (dispatcher-owned, built first)

Before dispatching any builder, the dispatcher turns the request into a numbered list of assertions. Each assertion is:

A<N> `<tag>`: <single checkable pass condition>

• A<N> — stable id (A1, A2, …) so every downstream dispatch and return can reference it verbatim.
• <tag> — how it will be proven. Exactly one of:
  • test — a passing automated test exercises it.
  • runtime-ui — observed in a running UI (DOM / screenshot / network), via browser-testing-with-devtools. Required for any visibility / placement / "appears in the table" assertion — static review does not satisfy it.
  • code-grep — proven by the presence/absence of a code pattern (e.g. "no exemplar-only branch remains without a sibling counterpart").
  • manual — a human must confirm; carries a requires_user_decision until they do.
• Pass condition — one observable fact, true or false. Split compound requirements into separate assertions so each can pass or fail independently.

Each dispatch receives the relevant assertions verbatim — never a paraphrase. The dispatcher advances only on assertions that are proven (see Artifact 3); anything unproven is treated as not done.

Worked example — "Retired/Disqualified behave like Walkover"

A request to make detailed scoring behave the same for all cancellation types (Walkover, Retired, Disqualified; excluding NotPlayed) becomes:

A1 runtime-ui: exactly one "detailed result" checkbox appears when any cancellation is
   selected, positioned below the winner selection.
A2 runtime-ui: A1 holds identically for Walkover, Retired, and Disqualified; excluded
   for NotPlayed.
A3 runtime-ui: a cancelled match with a detailed score entered shows that result in the
   standings table — for all three types.
A4 runtime-ui: the same match shows NO result in the round-robin / elimination view —
   for all three types.
A5 test: validation fires only when ≥1 detailed input is filled, then requires all
   companion fields.
A6 code-grep: no walkover-specific branch remains in display/validation without a
   Retired/Disqualified counterpart.

A2/A3/A4 are deliberately per-type — "works for Walkover" proves one third of each, never the whole. This is what stops the exemplar-only ship.

Artifact 2 — Parity / touchpoint inventory

For any "make X behave like existing Y" request, the exemplar (Y) is almost always special-cased in more than one place. Patch one site and the siblings stay broken — the run reports "done" and the user re-asks. To kill this:

1. Run a parity pass first — a deep-researcher recon that enumerates every site where the exemplar is special-cased: feature flags, branches, display logic, validation, translations, fixtures, tests.
2. Turn each site into an assertion — every listed site must be generalised to the whole set, and gets an assertion (usually code-grep for "no exemplar-only branch remains" plus a runtime-ui/test for the behaviour).
3. Re-run the proof across every member of the set — the verification for member A is repeated for B and C. A proof that only covers the exemplar does not close the assertion.

The inventory is dispatcher-owned: the dispatcher commissions it and converts it into assertions. Downstream specialists consume the inventory (confirm each listed site is covered) rather than independently re-deriving the call sites — re-derivation is exactly where sites get missed.

Parity inventory checklist
- [ ] Every exemplar special-case site enumerated (flags, branches, display, validation,
      translations, fixtures, tests) — by a deep-researcher pass, not a guess.
- [ ] Each site mapped to an assertion that covers the WHOLE set, not just the exemplar.
- [ ] The verification plan re-runs the same proof for every member of the set.
- [ ] A `code-grep` assertion guards against any exemplar-only branch surviving.

Artifact 3 — Structured upward return

Specialists end their work with a structured object, not prose-as-truth. Free-form "looks good / approved" summaries are what reported success over a broken feature; they are not accepted.

changed_files:        [path:line — 3–6 word note, …]
assertions_proven:    [A2: standings shows for Retired ✓ — evidence: <test name | screenshot | grep result>, …]
assertions_unproven:  [A4: round-robin hidden for Disqualified — NOT checked, …]
assertions_failed:    [A3: standings empty for Retired — evidence: <runtime observation>, …]
tests_run:            [command → result, …]
open_risks:           [non-blocking concerns, assumptions made, …]
requires_user_decision:[questions only a human can resolve, …]

Rules:

• An assertion may be listed under assertions_proven only if its evidence is named (test name, command output, file:line, or runtime observation). No evidence → it belongs in assertions_unproven.
• In the pi agent-hub harness, assertion-carrying dispatches are machine-parsed before the dispatcher sees them: the compact parsed object is surfaced as details.structuredReturn, the full raw output is written to .pi/agent-sessions/artifacts/returns/<agentKey>-run<N>.md and surfaced as details.returnPath, and evidence-less assertions_proven entries are flagged/demoted by details.contractNotices rather than accepted as proven. update_assertion(status: "proven") also validates evidence by assertion tag; for runtime-ui, evidence producers must save a runtime artifact under .pi/agent-sessions/artifacts/evidence/ and name that existing path.
• assertions_unproven and assertions_failed are reported honestly — never re-labelled as success to look finished. Half-done is more useful stated than hidden.
• The dispatcher advances only on assertions_proven. unproven and failed both mean not done and feed the next dispatch.

Artifact 4 — Requirement-regression reset

When the user says a delivered requirement is wrong again, the prior upward summaries are now known to be unreliable — do not build on them. Before any new dispatch:

1. Invalidate stale summaries — treat earlier "proven/approved" claims for the affected area as unverified.
2. Rebuild the assertion set from the latest correction — the newest user message is the source of truth; re-derive the affected assertions from it (a reversed instruction replaces, it does not append).
3. Re-run the parity inventory if the regression is a "behave like" case — the missed siblings usually live in a site the first inventory skipped.
4. Only then dispatch, with the rebuilt assertions passed verbatim.

How the artifacts connect

request ──→ [A1] build acceptance assertions (dispatcher)
   │            │
   │            └─ "behave like Y"? ──→ [A2] parity inventory (deep-researcher) ──→ more assertions
   ▼
dispatch builder (assertions verbatim) ──→ [A3] structured return (status + evidence)
   │                                              │
   │            ┌── all relevant assertions proven? ──┐
   ▼            │                                     │
gate per slice ─┴── no ──→ re-dispatch unproven/failed
   │
   └── runtime-ui assertion? ──→ require browser proof, not static review
        │
   "wrong again" from user ──→ [A4] regression reset ──→ rebuild assertions ──→ re-dispatch

The message-level protocols the dispatcher uses while enforcing this contract (sentinels, push events over polling, barriers, fan-in digests) are catalogued in references/fleet-coordination-patterns.md.

Common Rationalizations

Red Flags

• A dispatch goes out before the acceptance assertions exist.
• A "behave like Y" request proceeds without a parity/touchpoint inventory.
• A specialist returns a prose verdict ("looks good", "approved") instead of the structured object.
• An assertion is marked proven with no named evidence.
• A runtime-ui assertion is closed on static review / a code reading alone.
• The same defect is re-asked and the next dispatch reuses the old assertions/summaries unchanged.
• "Works for the exemplar" is reported as the whole requirement done.
• Verification covers code mechanics and the exemplar path (which has fixtures) but not semantic parity across the set or the runtime UI.

Verification

Before reporting an orchestrated task as done, confirm:

• A numbered acceptance-assertion list existed before the first builder dispatch, each with a tag and a single pass condition.
• Every "behave like Y" requirement produced a parity/touchpoint inventory, and each site became an assertion covering the whole set.
• Every specialist return was the structured object — assertions_proven entries each name their evidence.
• Every runtime-ui assertion carries an actual runtime observation (DOM / screenshot / network), not static approval.
• No assertion sits in assertions_unproven or assertions_failed at "done" — unproven means not done.
• On any "wrong again", the assertion set was rebuilt from the latest correction before re-dispatch.