Reduce

Reduce (De-abstraction for Agents)

Overview

Diagnose abstraction cost versus value and recommend lower-level primitives using a surgical, minimal-incision mindset.

Defaults:

• Optimize for agent-editability (few layers, explicit config, deterministic commands).
• Be aggressive: prefer primitives even if it increases short-term duplication or migration work.
• Preserve observable behavior unless the user explicitly requests a semantic change.
• Analysis/recommendations only; do not implement unless explicitly asked.

Double Diamond fit

Reduce is a Discover/Define-heavy skill that produces a concrete cut list and migration plan without writing code.

• Discover: inventory the abstraction stack and locate indirection points.
• Define: score each abstraction (agent-tax vs value) and choose keep/cut.
• Develop: select the next-lower replacement rung and the smallest reversible migration.
• Deliver: report an audit table + prioritized cut list + migration plan + minimal-incision patch suggestions.

Entry Criteria

Use this skill only when at least one condition is true:

• Change latency is dominated by abstraction/tooling hops rather than local readability.
• Behavior is controlled by framework hooks, plugins, codegen, or configuration indirection.
• The target outcome is to remove or downgrade layers while preserving observable behavior.
• The current interface is changing during interaction, but that evolution is hidden in ad-hoc runtime checks instead of explicit protocol/state boundaries.

Triage Gate

• Prefer $reduce for architecture/tooling de-abstraction and dependency cuts.
• Prefer $complexity-mitigator for local readability or control-flow simplification inside the current stack.
• If both apply, run $reduce first to delete layers, then simplify the residue.
• If interaction-dependent interfaces are core to the domain (session/capability/progressive protocol), reduce incidental wrappers first; do not flatten the protocol itself without proof.

Core Principles

• Minimal incision, maximal simplification: target the smallest change that deletes the most indirection.
• Agent-friendly primitives win: plain files, explicit config, simple CLIs, no hidden generators, no interactive prompts.
• Prefer deletion over replacement when behavior is unused or redundant (prove unused via repo evidence).
• Prefer one obvious path over flexible multiplexing (plugins, adapters, DI containers) unless value is proven.

Guardrails

• Default to repo-local evidence; do not guess usage/value.
• Do not recommend big-bang rewrites; require seams, phases, proof signals, and a rollback lever.
• Do not propose breaking external surfaces without a compatibility wrapper or an explicit user ask.
• Do not add tools/dependencies unless explicitly requested.
• If implementation is requested, hand off to $tk.
• Do not collapse an essential evolving interface into one global fixed interface unless the same observable protocol can be proven with deterministic tests.

What "Agent-editability" Means (practical)

An agent can:

• Find where behavior lives (few hops; few conventions; minimal magic).
• Change it with a small diff (no repo-wide cascading edits).
• Run/verify quickly (one deterministic command; minimal environment).

Non-goals (unless explicitly requested):

• Beautification refactors.
• Re-platforming for its own sake.
• Tuning performance/scale beyond what the existing contract requires.

Workflow

1. Discover: Map the abstraction stack

Inventory what makes change hard.

Required scan (repo-local):

• Toolchain: build/test commands, task runners, codegen, formatter/linter, monorepo tooling.
• Runtime: frameworks/meta frameworks, plugin systems, DI, reflection, middleware layers.
• Data: ORMs/query builders/migrations, caches, queues, service mesh.
• Frontend: SPA frameworks, bundlers, state libraries.
• Infra/deploy: k8s, Helm, Terraform layers, bespoke pipelines.

Evidence collection defaults:

• Prefer direct evidence: package.json scripts, Makefile/justfile, CI config, Dockerfile, deploy manifests.
• Trace one real request path: input -> validation -> core rule -> persistence -> output.
• Note every indirection point (codegen boundary, framework hook, config indirection, adapter layers).
• If interface evolution is suspected, trace at least 2-3 interaction paths and record how the allowed operation set changes after each response/event.

2. Define: Decide whether abstraction cost is too high

Classify each abstraction as: keep | wrap | slice | replace | delete.

Cost signals (agent-tax):

• Hidden steps: codegen, implicit conventions, runtime magic, reflection, decorators.
• Indirection: behavior lives in hooks/middleware/config rather than code you can edit.
• Tool weight: slow installs/builds/tests; large dependency graph; multi-tool orchestration.
• Non-determinism: environment-sensitive behavior, flaky tests, network-required dev loops.
• Churn risk: upgrades break frequently; generated diffs; brittle integrations.

Value signals (justification):

• Hard constraints: compliance, multi-tenant isolation, true scale needs, audited change control.
• Proven reuse: multiple independent consumers, stable shared domain rules.
• Operational leverage: materially reduces oncall risk (with evidence).
• Protocol realism: allowed operations genuinely change with interaction state (for example session phase, capability grants/revocations, adaptive UI state, progressive model stages).

Scoring rubric (make cut decisions mechanical):

• Agent-tax score (T): 0-3
  • 0 = negligible (direct code; obvious entrypoints; no extra tools)
  • 1 = mild (one extra layer; still searchable; deterministic commands)
  • 2 = high (codegen/indirection; slow loops; multi-tool orchestration)
  • 3 = severe (hidden magic; multiple generators; interactive/manual steps; flaky loops)
• Value score (V): 0-3 (score 0 if you cannot cite evidence)
  • 0 = unproven/optional (no tests/docs/callsites/ops evidence)
  • 1 = convenience (small DX win; could be replaced without changing the contract)
  • 2 = proven leverage (multiple consumers; reduces a bug-class; real ops benefit)
  • 3 = mandatory (compliance/legal requirement; SLO-critical; audited change control)
• Delta (D) = T - V

Default verdict mapping (aggressive, but not reckless):

• D >= 2: replace or delete (prefer delete if unused)
• D == 1: slice now, replace next (or wrap to isolate first)
• D == 0: wrap or slice (reduce surface area and remove sharp edges)
• D == -1: keep, but simplify interfaces/entrypoints
• D <= -2: keep

Definitions (verdicts):

• keep: retain abstraction; reduce incidental friction (docs, scripts, entrypoints).
• wrap: keep internally, but put a stable adapter in front to localize future removal.
• slice: remove optional flexibility (plugins, multi-variant configs) to the one proven path.
• replace: swap for a lower-level primitive with a migration seam.
• delete: remove entirely.

Aggressive default policy:

• If value is not proven (tests/docs/callsites/ops evidence), treat it as optional and recommend reduction.
• If the abstraction exists "for flexibility" but only one variant is used, inline to the one variant.
• If an abstraction exists to prevent duplication but adds hops/tooling, prefer duplication.

Evidence-confidence modifier (required before final verdict):

• Confidence level (C): high | medium | low
  • high: constraints/value are proven with repo-local evidence (tests/docs/callsites/ops config).
  • medium: partial evidence exists, but at least one critical assumption is inferred.
  • low: external obligations are plausible (compliance/SLO/audit/runtime policy), but not proven locally.
• External-obligation guardrail:
  • If C=low and verdict is replace or delete, cap to slice or wrap until one of these is true:
    • explicit user approval to change external obligations, or
    • evidence proving no such obligations exist.
• Report confidence in the audit row notes for every replace/delete recommendation.

Interaction-evolution guardrail:

• If evidence shows interface evolution is essential (state-dependent allowed operations), treat that protocol boundary as core domain structure.
• In that case, prefer slice/wrap on incidental tooling around the protocol before attempting replace/delete of the protocol model itself.

3. Develop: Propose lower-level replacements

Pick the next lower rung on the replacement ladder (avoid big-bang rewrites).

Replacement ladder (common moves):

• Meta framework -> framework -> stdlib primitives.
• Codegen -> checked-in artifacts + small deterministic generator (or delete entirely).
• ORM -> query builder -> parameterized SQL.
• GraphQL -> REST/JSON -> RPC -> direct function calls (internal only).
• Implicit runtime gating -> explicit state-indexed protocol map (operation set per state) -> optional typed client/session wrappers.
• SPA -> server-rendered pages -> static HTML/CSS/JS.
• k8s -> Docker Compose -> single process + systemd (or platform native).
• Monorepo tool -> package-manager workspaces -> plain scripts.
• DI container -> explicit constructors/wiring.
• Custom DSL -> JSON/YAML/TOML with a small parser + schema.

Deconstruction patterns (agent-centric):

• "Make the invisible visible": replace conventions with explicit entrypoints and wiring.
• "Collapse configuration": many layers -> one canonical config file (with comments only if unavoidable).
• "Delete the orchestrator": replace toolchains with a single scripts/dev and scripts/test (or make dev/test).
• "Strangler seam": introduce a stable adapter boundary; implement the primitive behind it; migrate callers incrementally.
• "State-index the protocol": move scattered runtime checks into one explicit transition table (state x operation -> next state).

4. Deliver: Report findings and recommendations

Default output must include:

1. Abstraction audit (table).
2. Cut list (prioritized).
3. Migration plan (phased + proof signals + rollback).
4. Patch suggestions (minimal incisions; file/command level; no implementation).

Output Profiles

Use one profile per response.

• Full profile (default): use the complete format in Output Format (default full profile).
• Quick profile (small audits): use only when both conditions hold:
  • Scope is narrow (<=3 abstractions or one subsystem), and
  • The user asked for concise/minimal output.

Quick profile sections (exact order): 0) Scope + assumptions 1) Top Abstractions (mini-audit) 2) First Cut Recommendation 3) Minimal Migration + Rollback 4) Risks / unknowns

Quick profile minimums:

• Still include T/V/D for each listed abstraction.
• Still cite repo-local evidence (or explicitly mark missing evidence).
• Still provide one deterministic proof signal.
• If interface evolution is in scope, include one compact state-transition sketch (table or bullets) before final cut recommendations.

Output Format (default full profile)

Use these exact section headers in order. If evidence is missing, keep the header and write Not enough repo evidence yet. rather than omitting sections.

0) Scope + assumptions

• In-scope surfaces: ...
• Out-of-scope: ...
• Constraints discovered: ...

1) Abstraction Audit (table) Include one row per abstraction.

Notes:

• "Value" must cite repo-local proof: tests/docs/callsites/ops config.
• If you cannot cite evidence, score V:0.
• "Verdict" must be one of: keep | wrap | slice | replace | delete.

2) Cut List (prioritized)

• P0 (delete first): ...
• P1: ...
• P2: ...

Each item must include: expected simplification, blast radius, and fastest proof signal.

3) Migration Plan (per cut item) For each P0/P1 item:

• Seam/boundary: ...
• Phase 1 (reversible): ...
• Phase 2 (switch traffic/callers): ...
• Phase 3 (delete old path): ...
• Proof signals: ... (tests/build/run)
• Rollback lever: ...

4) Patch Suggestions (minimal incisions; no code) List concrete, reviewable edits:

• Files to add/modify/delete: ...
• Commands to run (deterministic): ...
• What "done" looks like (signal): ...

5) Risks / limits

• ...

Replacement Patterns (Examples)

• React/SPA for a small static site -> HTML/CSS/JS, no build step.
• Headless CMS for small docs/marketing -> Git + Markdown (+ static site generator if truly needed).
• ORM for simple CRUD -> parameterized SQL queries.
• GraphQL for a single client -> REST/JSON endpoints.
• State management framework for a small UI -> local state with explicit event handlers.
• Heavy task runner -> scripts/* or Makefile with 3-5 canonical commands.
• Multi-layer config system -> one config file + a small loader.
• Scattered auth/runtime guards -> explicit session-state protocol map (Anonymous/Authed/etc.) + thin per-state adapters.
• Dynamic capability checks spread across services -> capability-state transition table + adapter selection keyed by capability state.

Interaction-Evolving Interface Addendum

Use this when the system's interface changes as a result of interaction.

Detection checklist:

• The allowed operation set changes after specific responses/events.
• Current behavior relies on distributed if authorized, feature flag, or capability checks across many call sites.
• Clients must "guess and fail" at runtime instead of knowing legal next operations from state.

Recommendation policy:

• Preserve essential protocol evolution; reduce incidental machinery around it.
• Prefer explicit protocol boundaries:
  • state x operation -> next_state
  • allowed responses per operation
  • adapter rules (act) and state updates (upd) for integration points
• Cut targets first: duplicated wrappers, hidden indirection, multipath config, and non-deterministic orchestrators around the protocol.

Proof signals for this mode:

• Depth-bounded trace tests (at least to depth 3) over legal transitions.
• One negative test proving an invalid transition is rejected or unrepresentable.
• Compatibility check showing a fixed-interface simplification (if proposed) preserves observable traces.

Real Trigger Phrases (from session prompts)

Use these phrases as natural-language routing cues for $reduce:

• "It just feels over-engineered for what I want. Is there a way you can see that we could start simpler and build things back up?"
• "I really want to reduce the size of the codebase before building it back up."
• "Only the minimal needed to support what is needed to remain."
• "How much could we simplify things?"
• "Brilliant or over-engineered?"

Weekly re-measure loop:

• Baseline and trend:
  • seq skill-report --root ~/.codex/sessions --skill reduce --snippets 20
• Prompt-cue hit sampling:
  • seq query --root ~/.codex/sessions --spec '{"dataset":"messages","where":[{"field":"role","op":"eq","value":"user"},{"field":"text","op":"regex_any","value":["(?i)over-?engineered","(?i)start simpler","(?i)reduce the size of the codebase","(?i)minimal needed","(?i)simplify things"]}],"select":["timestamp","path","text"],"sort":["-timestamp"],"limit":50,"format":"jsonl"}'
• After one week, compare cue-hit samples and update frontmatter trigger examples only if precision improves.

Questions (Judgment Calls Only)

• Research first; do not ask for discoverable facts.
• Ask only judgment calls, prefer 1 question, max 3.
• Use request_user_input when available; otherwise ask in a short numbered block.

Good questions (examples):

• "Can we accept some short-term duplication to delete this framework (recommended: yes)?"
• "Is it acceptable to add a compatibility wrapper so external callers remain stable (recommended: yes)?"
• "Is infra allowed to change, or is this strictly code-level (recommended: code-level only)?"

Handoffs

• If trade-offs remain unclear, invoke $creative-problem-solver.
• If implementation is requested, hand off to $tk.

Pitfalls

• Generic advice without locations/evidence.
• Big-bang rewrites without seams, proof signals, and rollback levers.
• Removing abstractions that are carrying compliance/ops obligations (without a replacement plan).

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