AG

agent-protocol

A structured workflow for using multiple sub-agents to clear project backlogs efficiently through orchestration.

Install

mkdir -p .claude/skills/agent-protocol-sicambria && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/17406" && unzip -o skill.zip -d .claude/skills/agent-protocol-sicambria && rm skill.zip

Installs to .claude/skills/agent-protocol-sicambria

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Multi-agent backlog-draining protocol. Triage → ground → advisor → cluster → spawn one wave → serialize-integrate → run to exhaustion → retro-of-retros → document skips. Delegates independent work to a fleet of agents that each plan+implement in a worktree, then integrates their branches serially through the orchestrator with adversarial verification.
353 charsno explicit “when” triggerlonger than Claude Code's old 250-char listing cap (fine on current versions)
Advanced

Key capabilities

  • Triage open items across the repository's backlog surface
  • Cluster do-now items into disjoint-domain groups
  • Spawn agents concurrently, each with a self-contained prompt
  • Integrate results serially through the orchestrator
  • Run waves to exhaustion
  • Conduct a retro-of-retros to improve the workflow

How it works

The protocol triages backlog items, clusters independent tasks, and then spawns concurrent agents to plan and implement solutions. Results are integrated serially, and the process includes a retro-of-retros to refine the workflow.

Inputs & outputs

You give it
backlog of independent items
You get back
integrated results from delegated agents and a retrospective

When to use agent-protocol

  • Drain a large backlog of independent issues
  • Execute parallel development tasks
  • Run cross-verified feature implementation waves

About this skill

agent-protocol

A named, repeatable mechanism for draining a backlog with a fleet of delegated agents: triage every doable item, cluster the independent ones, have a stronger reviewer sharpen the plan, delegate each cluster to an agent that plans + implements, integrate results serially through the orchestrator, run waves to exhaustion, then close with a retro-of-retros that improves the workflow itself.

Exists because parallel delegation silently degrades without discipline: agents self-merge into races, ship confident no-ops, and drop work on timeouts that looks like failure but isn't. The phases and invariants below are the scar tissue that keeps a wave honest.

This skill is the harness-native form. All stack specifics resolve through .harness/config.json and AGENTS.md — never assume a fixed toolchain command.

When to invoke

  • You have a backlog of independent items — open plans in the active plans dir, open findings under the learning-loop dirs, a TODO/audit sweep — where several can proceed without blocking each other.
  • The work benefits from parallelism + independent verification, not one linear edit.
  • The user has explicitly opted into multi-agent orchestration — this spends real tokens across many request streams. Do not self-trigger it for ambient work.

Do not invoke for a one- or two-file change you can finish inline, or when every remaining item is genuinely gated/serial.

Grounding (read once at the top of the run)

  • Read AGENTS.md and .harness/config.json. Resolve, from config:
    • defaultBranch — the branch agents must never commit to directly (worktree-first).
    • verify contract — the real test/lint/build/e2e/healthcheck checks, run via .harness/scripts/verify.mjs. This is the marquee gate; there is no hardcoded command.
    • plan.dirs.active / plan.dirs.worktrees / plan.dirs.done — plan lifecycle folders.
    • plan.claimsFile — the worktree claims ledger (who owns what).
    • plan.evidenceHeading and plan.dimensions — the evidence section every plan carries and the configured dimensions to cite (see phase 5; do not hardcode a dimension count).

The nine phases

1. Triage

Enumerate every open item across the repo's backlog surface — open plans in the active plans dir, open findings under the learning-loop dirs (docs/audits, docs/errors, or the .harness/archive/* equivalents per config), and any explicit TODO/audit sweep the scope names. Classify each:

  • Do-now — unblocked, positive cost-benefit, fits a disjoint domain.
  • Skip — gated (product/data/infra), low cost-benefit, or infeasible. Document the reason and a rough score for every skip. Skips are recorded, never silent (phase 9).
  • Route-to-config — anything whose only effect is scanner/linter noise goes to the relevant exclusion/suppression config with a scoped rationale, not to an agent task. Never fake a suppression to make noise disappear; if the mechanism can't be validated (server down, gate unavailable), document the deferral and log it under .harness/archive/decisions/.

2. Ground (grep-before-build)

Before composing any wave:

  • grep/read each do-now candidate's marquee target — retire anything already done.
  • Confirm the named gap is real — don't trust a ledger entry blindly.
  • Confirm a green base tip: git log -1, run the verify contract (.harness/scripts/verify.mjs), and pin the commit — every agent branches from it.
  • Identify uncontrolled / live agents (git worktree list --porcelain) and mark their domains off-limits for this wave.

3. Advisor

Write the plan out, then call advisor(). Adopt its blocking fixes before spawning. The advisor sees the whole transcript and catches sequencing/concurrency errors the plan glosses over (it is the mechanism that forces the serialize-merge model and pulls a hard-fail gate flip out of a concurrent wave).

4. Cluster

Partition do-now items into disjoint-domain clustersno two clusters edit the same file. Watch shared/ratchet files: manifests (package.json, lockfiles), baseline/budget JSON, registries, CI workflows, and plan.claimsFile. Assign a model per cluster:

  • Default: omit the override and inherit the session model.
  • Downshift to a cheaper/faster model only for squarely mechanical or docs-only clusters (ratchet edits, config wiring, standard authoring).
  • Keep the strong model for judgment-heavy spikes, behavioral-regression-risk refactors (need differential evidence), and security / gate-hardening / latent-gap detection.

Defer clusters that touch a live agent's domain or share a ratchet file with another cluster — run them in a later wave.

5. Spawn (one wave)

Launch the wave's agents concurrently, each with a self-contained prompt (fresh contexts inherit no memory or prior-wave scar tissue — the prompt must carry every rule) enforcing the per-agent lifecycle:

  1. git worktree add <wt> -b <branch> <PINNED_BASE> and record the claim in plan.claimsFile.
  2. Bootstrap the worktree per the repo's init path (.harness/ scripts / AGENTS.md).
  3. Write a plan inside the worktree under plan.dirs.worktrees, including the evidence section named by plan.evidenceHeading. Cite every dimension configured in plan.dimensions (currently the core set — Tests / shift-left, Reused patterns / grounding, Security — but read config; the list is dynamic) with an inline path:line citation that resolves against the working tree, or an explicit N/A — reason. A hallucinated citation hard-fails the commit.
  4. Implement — stay strictly in-domain.
  5. Verify in-worktree: run the full .harness/scripts/verify.mjs contract plus the cluster's own marquee adversarial gate, run explicitly. A "changed/related-only" check is a subset of the full gate — passing it is necessary, not sufficient. Do not use the remote/CI gate as a serial discovery probe; run the push-only checks locally first.
  6. Commit plan+code on the branch with real hooks (never --no-verify).
  7. Return BRANCH READY: <path> | <branch> | <summary> | gates: <passed>do NOT self-merge. Return SKIP: <reason + cost-benefit> if infeasible.

If an agent writes an incident/RCA note, it must register it in the same commit so it doesn't block siblings on shared default-branch gates.

A returning agent self-verifies (runs its gates) but never self-approves — approval is a separate role (phase 6). Doer ≠ reviewer: no agent's own work is the sole thing gating its own merge. This is the fleet form of Liza's per-task doer/reviewer pairing — the doer produces the branch; a distinct reviewer (the orchestrator, or a dedicated reviewer agent for significant work) approves it.

6. Serialize integration + review quorum (the orchestrator's job)

Merge branches one at a time through yourself — never let agents self-merge when an uncontrolled agent shares the default branch:

  • --no-ff merge one branch, then verify the default branch is green (run the verify contract) before the next.
  • Adversarially review every returned branch — agents return confident no-ops. Run the branch's marquee gate yourself; don't trust the summary. Confirm the mechanism is real, not just that a file changed.
  • Review quorum, scaled to blast radius. Standard cluster → 1 reviewer (the orchestrator's adversarial pass above). Significant/architectural cluster — security, gate-hardening, behavioral-regression-risk, or a wide blast radius (consult the Protection Matrix, .harness/INVARIANTS.md) — requires 2+ independent reviewers. If reviewers split, the branch is partially_approved: do not merge — surface the disagreement and escalate (reframe or ask), never average it away. Impact discovered mid-review that lifts a cluster into "significant" escalates its quorum on the spot.
  • Provider diversity (soft, L5). When .harness/config.json → agents lists more than one provider and review.providerDiversity is enabled, prefer a reviewer of a different provider than the branch's author — cross-model review defeats shared blind spots. Soft preference, never a hard gate: a single-provider repo simply reviews with what it has.
  • Hold, don't stack, if a contended index is locked or a sibling left the default branch red.

7. Run to exhaustion

Repeat phases 4–6 in waves until the unblocked backlog is drained or every remaining item scores low cost-benefit. Re-ground (phase 2) at the top of each wave — earlier waves may have closed or unblocked later items.

8. Retro-of-retros

A read-heavy synthesis across all wave reflections + this run's integration notes: extract cross-wave patterns the per-wave retros missed and turn them into concrete workflow/standard/memory improvements. Append the run's retro under .harness/archive/retros/, and promote durable heuristics into .harness/memory/procedural/ — that is the home that survives context resets (per AGENTS.md); a session-scoped note evaporates on compaction.

9. Document & close

  • Record every skip with its reason (and score) on the backlog surface it came from.
  • Move shipped plans plan.dirs.worktreesplan.dirs.done and clear their entries from plan.claimsFile; repoint any references so docs checks stay green.
  • Log any gate override during the run under .harness/archive/decisions/ — an override that leaves no trace is forbidden.
  • Run the repo's closeout/verify pass and confirm the default branch is green.

Invariants (learned empirically — violate these and the run silently degrades)

  1. Serialize the merge when you don't own every agent. Self-merge only ever worked because prior waves controlled the whole environment. With an uncontrolled agent on the shared default branch, agents r

Content truncated.

When not to use it

  • One- or two-file changes that can be finished inline
  • When every remaining item is genuinely gated or serial
  • Ambient work that does not explicitly opt into multi-agent orchestration

Limitations

  • Spends real tokens across many request streams
  • Requires explicit opt-in for multi-agent orchestration
  • Does not allow agents to self-merge

How it compares

This protocol provides a structured, multi-agent approach with adversarial verification and serial integration for draining backlogs, contrasting with ad-hoc parallel delegation that can lead to silent degradation.

Compared to similar skills

agent-protocol side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
agent-protocol (this skill)019dNo flagsAdvanced
autonomous-agents106moNo flagsAdvanced
agent-goal-planner25moNo flagsAdvanced
planner15moNo flagsIntermediate

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Example prompts that trigger this skill in your AI assistant.

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