Haiku Pilot — Default-Haiku Execution Playbook

Thesis

Weak planner + strong delegation > strong planner doing everything.

AgentOpt (arxiv 2604.06296): On HotpotQA, Opus alone = 31.71%; Ministral 3 8B planner + Opus solver = 74.27%. Augment Code eval (2026-04): Best-quality AGENTS.md provides performance gain equivalent to one model tier (Haiku → Sonnet effective).

→ Default parent session to Haiku 4.5; aggressively delegate to sub-agents; escalate only on quantitative gate trigger.

"Documentation / process design improvements ≥ model upgrade" is the engineering basis. Blindly upgrading models in multi-stage pipelines often reduces performance (planner doesn't delegate).

Per-Session Pre-flight (run once per task)

1. Reference Pattern Technique

Why it matters: Haiku diverges easily from abstract descriptions; pointing to a concrete file = strongest possible context.

2. Think-Before-Coding (compensates Haiku tendency)

Before implementation, output:

• 1–2 sentence task understanding restatement (your interpretation, not parroting)
• Key assumptions (≥ 1, prefixed with "Assumption: ...")
• If multiple interpretations are reasonable → list options for user confirmation, don't pick one yourself

Source: core.md § "Think-Before-Coding". Haiku tends to skip this step; this SKILL enforces it.

3. Diff-Review Pledge

Before declaring "complete", run:

git diff --stat
git status

Explain each change in one sentence. Catches Haiku quietly modifying out-of-scope files (surgical-changes discipline).

4. Citation Anchor Enforcement

When citing wiki / docs / spec for numbers, conclusions, or anti-patterns, attach a structured anchor:

• (P0X §Y.Z) — paper section ref (e.g. (P03 §4.2)) — preferred for paper-grounded citations
• (<source> Step N) — wiki step number
• (anti-pattern #N) — wiki anti-pattern number
• (<file>:line-range) — code / config line ref

Anchor count requirement (per answer paragraph):

• Easy / medium tasks: ≥ 3 structured anchors
• Hard tasks (architecture / counter-factual / synthesis): ≥ 5 structured anchors — (P0X §Y.Z) format strongly preferred

If no precise anchor available → tag [unverified]. Never fake a source. Violation: retry that paragraph; do NOT declare done.

Empirical basis: anchor density discrepancy is the primary driver of citation accuracy variance between Haiku and Sonnet/Opus on benchmark tasks. 2026-05-08 6-agent 10Q benchmark: Haiku-Pilot hard-question anchor density collapsed from 7/100w (medium) to 1/100w (hard), the primary D2 gap (−1.0) vs vanilla Opus. Pre-flight previously did not require ≥ 5 anchors on hard tasks; this rule closes that gap. Per-source-type anchor vocabulary (wiki / code / API doc / RFC / paper): see shared reference anchor-dictionary.md (suite-internal) if available.

5. Source-Verify Loop (required for citation tasks)

After drafting an answer that cites numbers, model names, or verbatim quotes, run this 3-step loop before declaring done:

1. Identify: list every numeric / proper-noun citation in your answer (e.g. "31.71%", "Claude Opus 4.6", "≥ 100 lines").
2. Grep: for each citation, run grep -i "<number-or-name>" <source-path>. If absent → the citation is fabricated.
3. Record: in the self-check table § "Source-verify" row, mark ✓ only when every citation passes step 2.

If any cited number fails grep, rewrite that paragraph before completion. Do not ship with [unverified] tags as a workaround on citation tasks; the gate is binary.

Empirical basis: 2026-05-06 v0.2.1 benchmark — 5 of 20 haiku-pilot responses (25%) shipped fabrications, capping Haiku→Opus gap closure at 45.3%. Adding this gate is the highest-ROI lever per gap analysis.

6. Content-First Structure (not Template-First)

Forbidden: filling every question with a fixed sub-heading template; restating in prose what the table already says.

Use instead: the question's nature determines the structure:

• Single decision → bulleted list
• ≥ 3 anti-patterns → 1 combined table (with "trigger / solution / Lab vs Prod" columns), NOT N separate tables
• Multi-option comparison → table lists only "final decision + exclusion rationale", does NOT enumerate all rejected options
• Emoji budget: ≤ 3 per section (✅/❌/🔴); neutral statements get none

Empirical basis: template-first wastes ~30% tokens AND lowers detail density vs content-first.

Per-Task Router (decision table → existing skills)

This router does NOT duplicate the full skill directory. See your workspace's skill resolver / index for the full list.

Task-Type Fast-Path (skip mandatory pre-flight when overhead > value)

Empirical basis: 2026-05-06 v0.2.1 benchmark Q04 — vanilla Haiku at 51/60 (135w) beat haiku-pilot at 49/60 (182w) on a 4-number recall. Fast-path captures this region by skipping pre-flight overhead on tiny answers.

Coding tasks

Research tasks

Review tasks

Docs tasks

Customize for your workspace: replace agent names with the agents that exist in your .claude/agents/ directory. If you don't have specialized agents yet, the general-purpose agent + a model override works