request-immunity

name	request-immunity
description	Request immunity patterns for user-facing agents — tier selection (T1/T2/T3), Phase 0 injection templates, and RV gate definitions. Use when creating user-facing agents, injecting request validation, or checking immunity gate compliance.

Request Immunity

Standard for preventing user-facing agents from acting on inconsistent, incomplete, ambiguous, or misleading requests. Every user-facing agent MUST include a Phase 0 that validates requests before execution. Validation intensity scales with the agent's exposure to freeform input.

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When to Use This Skill

• Creating a user-facing agent that needs request validation
• Selecting the appropriate immunity tier (T1/T2/T3) for an agent
• Injecting Phase 0 validation patterns into an agent's methodology
• Checking RV-1 through RV-4 quality gates on existing agents
• Reviewing whether an agent's request immunity matches its exposure level

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Methodology

Phase 1: Tier Selection

Agent Characteristic	Tier	Approach	Required Assets
Handles freeform strategy/design/analysis requests with open scope	T1: Full	request-evaluation skill (full methodology) → mode-interactive for critical gaps	request-evaluation + mode-interactive skill refs
Executes specific tasks but user-invokable with potentially vague input	T2: Input	request-evaluation skill inline → mode-interactive if gaps	request-evaluation + mode-interactive skill refs
Narrow scope, well-defined target, low ambiguity surface	T3: Scope	Inline target identification check → ask if target unclear	None — self-contained

Decision rules:

• Primary input is freeform natural language with open scope → T1
• Clear action verb but scope/target may be vague → T2
• Well-defined narrow scope that just needs a target → T3
• When in doubt → choose one tier higher

Phase 2: Inject Pattern

Select the injection pattern matching the chosen tier.

T1: Full Validation

Inject as Phase 0: Request Validation in the agent's methodology:

1. **Complexity check** — Single clear action with obvious scope?
   - YES → bridge minor assumptions, note them, proceed
   - NO → continue to step 2
2. **Apply `request-evaluation` skill** (full methodology) — Context Decomposition, Deliverable Analysis, Gap Detection, Challenge & Bridge
3. **Process results**:
   - No critical gaps → proceed with bridged assumptions documented
   - Critical gaps → apply `mode-interactive` skill to present gaps as questions
4. **Proceed** with validated, gap-free request

Agent constraints: add request-evaluation + mode-interactive skill references.

T2: Input Validation

Inject as Phase 0: Input Validation in the agent's methodology:

1. **Sufficiency check** — Apply `request-evaluation` skill (Context Decomposition only):
   - Target identifiable? (file, module, feature)
   - Action clear? (what to do)
   - Scope inferable? (how much)
2. **Bridge** — If 1-2 gaps resolvable from project conventions → bridge, note assumptions
3. **Escalate** — If target OR action undetermined → `mode-interactive` with 1-2 focused questions
4. **Proceed** with validated input

Agent constraints: add request-evaluation + mode-interactive skill references.

T3: Scope Validation

Inject as Phase 0: Scope Validation in the agent's methodology:

1. **Target identification** — Can I determine the specific target?
   - Path, module, error context, or plan reference available? → proceed
   - Multiple candidates? → ask: "Which {target type} should I focus on?" (list candidates)
   - No target? → ask: "What would you like me to {action verb}?"
2. **Proceed** with identified target

No additional assets required — pattern is self-contained.

Phase 3: Verify RV Gates

After injection, verify all 4 request immunity gates pass:

Gate	Check	Fail Condition
RV-1	Phase 0 exists	Methodology doesn't start with request/input/scope validation
RV-2	Tier appropriate	Validation tier doesn't match agent's freeform input exposure
RV-3	Assets wired	Required skills (request-evaluation, mode-interactive) missing from frontmatter/constraints
RV-4	Escalation path	Agent can't surface unresolvable gaps to user

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Anti-Patterns

• ❌ Skipping Phase 0 — Agent jumps straight to execution without validating request → wasted work on wrong target
• ❌ Over-tiering — T1 validation on a narrow-scope agent → unnecessary overhead, slows simple tasks
• ❌ Under-tiering — T3 on an open-scope agent → misses ambiguity, acts on assumptions
• ❌ Missing asset wiring — Selecting T1/T2 but not adding skill references → Phase 0 can't execute
• ✅ Right-sized validation — Match tier to actual freeform input exposure, wire required assets, verify RV gates