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intent-router

Classify the information-need of a query and dispatch it to the appropriate retrieval or reasoning strategy. Use before read-side memory access, before multi-strategy retrieval, or any time you'd otherwise default to "one retriever for everything". Returns a strategy label, a token budget, and a retrieval depth so downstream handlers can be specialised. Backed by Pre-Route (arxiv 2605.10235v2) and MemFlow (arxiv 2605.03312v1), which together show LLMs possess latent routing ability elicitable via a structured prompt — and that externalising the routing decision improves small-model performance by ~2x. Triggers: "route this", "what strategy", "before retrieving", "intent classification", or any query whose ideal handling depends on what KIND of question it is.

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Dépôt
Tibsfox/gsd-skill-creator
Dernière activité de la source
4 juin 2026 à 20:18
Langue détectée de SKILL.md
anglais
Étoiles
70
Forks
9

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SKILL.md
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name
intent-router
description
Classify the information-need of a query and dispatch it to the appropriate retrieval or reasoning strategy. Use before read-side memory access, before multi-strategy retrieval, or any time you'd otherwise default to "one retriever for everything". Returns a strategy label, a token budget, and a retrieval depth so downstream handlers can be specialised. Backed by Pre-Route (arxiv 2605.10235v2) and MemFlow (arxiv 2605.03312v1), which together show LLMs possess latent routing ability elicitable via a structured prompt — and that externalising the routing decision improves small-model performance by ~2x. Triggers: "route this", "what strategy", "before retrieving", "intent classification", or any query whose ideal handling depends on what KIND of question it is.
user-invocable
true
version
1.0.2
format
2025-10-02T00:00:00.000Z
triggers
["route this query","what retrieval strategy","what reasoning strategy","intent classification before retrieval","front-run the memory access"]
updated
2026-05-16T00:00:00.000Z
status
ACTIVE
source
arxiv 2605.10235v2 (Pre-Route), 2605.03312v1 (MemFlow)
# Intent Router ## Why The 2026 frontier converges on one architectural shift: **route → strategy → act**, replacing the historical *one-retriever-for-everything* pattern. Different query intents demand categorically different handlers: - **lookup** — direct factual recall, single retrieval, small budget - **multi-hop** — chain through intermediate facts, deeper retrieval, larger budget - **global** — summarise/aggregate across a broad slice, retrieve broadly + compress - **verification** — check a claim against evidence, retrieve narrowly + compare - **deep-reason** — escalate to a higher-tier model, retrieve generously, allow chain-of-thought - **lexical** — exact-match / keyword (BM25 territory), no embedding, narrow budget The empirical claim: a single fixed strategy is dominated on every axis by the conditional strategy. ## How Before any memory access or multi-strategy retrieval, run a structured-prompt classification pass that returns: ```json { "strategy": "lookup|multi-hop|global|verification|deep-reason|lexical", "token_budget": 2000, "retrieval_depth": 5, "refinement_policy": "none|verbal-rerank|consensus-check", "confidence": 0.0 } ``` If confidence < 0.6, fall back to the broadest strategy (`global`) so the system degrades gracefully rather than mis-routing. ### Output format vs confidence The full JSON envelope is the canonical form when downstream consumers read it programmatically (typed pipelines, gating code). For inline human-facing routing decisions, taper the ceremony to match the confidence: - **confidence ≥ 0.9** — emit just the strategy label on one line (e.g., `route: lexical`). The other fields default; don't print the envelope. - **0.6 ≤ confidence < 0.9** — emit the strategy + 1-line rationale. Skip the JSON. - **confidence < 0.6** — emit the full JSON envelope with the `global` fallback explicit. This is the only case where the structured output earns its tokens. Rationale: a CTA audit (`.planning/patterns/skill-audits/intent-router-2026-05-16.md`) found that high-confidence lexical-class probes produced full JSON envelopes that downstream consumers did not read. The output was surface-anchoring without information gain. ## When to skip - You're already in a typed pipeline whose strategy is fixed (e.g., a search command that's explicitly lexical). - The query is short enough that the routing call costs more than it saves (rule of thumb: < 20 tokens of question text). - **Scoped exact-match lookup in a known directory** — the surface form is so cleanly lexical that classification cannot change the outcome. Triggers: "find files in `src/X/` that contain literal string `Y`", "grep for `Z` under `path/`", "list all files referencing `IDENT`". The routing decision is structurally pinned to `lexical`; just `grep`. Added 2026-05-16 from CTA audit (`.planning/patterns/skill-audits/intent-router-2026-05-16.md`) — the bounded probe showed the routing ceremony added overhead without changing the action. - You're in a streaming/interactive context where added latency dominates the routing payoff. ## Integration - `wrap:execute` and `wrap:verify` — invoke intent-router as the FIRST step in handler dispatch. - `gsd-graphify` — already does query routing internally; intent-router exposes the same primitive uniformly to other skills. - Future `src/memory/strategies/` directory will be the typed substrate; this skill is the policy on top. ## Cross-references - Rosetta concept #7 (Intent Routing) — canonical definition - College: `agent-systems / agent-memory / agent-intent-routing` - Related skills: `graphify` (when query is graph-shaped), `gsd-explore` (when intent is exploratory)
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