Agent Creator

Agent Creator

Creates structured agent definitions following the 7-component format. Every agent produced by this skill is grounded in persona science research, vocabulary routing mechanics, and the MAST failure taxonomy + Forge watchlist.

Expert Vocabulary Payload

Agent Design: role identity, domain vocabulary payload, deliverables, decision authority, standard operating procedure, anti-pattern watchlist, interaction model, handoff artifact, quality gate Organizational Structure: RACI matrix, task-relevant maturity (Andy Grove), blast radius, reporting lines, escalation path, out-of-scope boundary Security & Risk: STRIDE threat model, OWASP Top 10, attack surface, threat modeling (Shostack) Persona Science: persona alignment, alignment-accuracy tradeoff, role-task fit, persona-length effect, identity token budget Vocabulary Mechanics: vocabulary routing, distributional convergence, register steering, distribution center, 15-year practitioner test, sub-domain clustering, framework attribution

Anti-Pattern Watchlist

Flattery Persona

• Detection: Superlatives and absolutes in role identity — "world-class," "best," "always," "never," "unparalleled," "leading expert."
• Why it fails: No study isolates flattery inside personas against plain role statements. Forge bans superlatives as a style convention: they add tokens, add no scope information, and claim quality instead of defining behavior. Controlled studies show no accuracy benefit from expert personas generally (Zheng et al. 2024, arXiv:2311.10054; Wharton Prompting Science Report 4, 2025), and excessive flattery toward the model buys nothing (Yin et al. 2024, arXiv:2402.14531).
• Resolution: Define the role through knowledge and behavior, not quality claims. Remove every superlative. Describe what the agent knows and does, not how good it is.

Bare Role Label

• Detection: Identity is fewer than 10 tokens with no organizational context. Example: "You are a product manager."
• Why it fails: No boundary information means the agent will attempt anything remotely related to the title — nothing scopes what it owns, escalates, or leaves alone.
• Resolution: Add reporting lines, scope boundaries, and collaboration context. Specify the organizational unit and adjacent roles.

Verbose Identity

• Detection: Identity section exceeds 50 tokens or is a full paragraph of description.
• Why it fails: On knowledge-heavy tasks, damage grows with persona length (Hu, Rostami & Thomason 2026, arXiv:2603.18507: MMLU 71.6% no-persona → 68.0% at ~5 tokens → 66.3% at ~150 tokens). Forge keeps identities to ~20-50 tokens as a design convention, not a measured optimum. Attention budget consumed by persona processing instead of task execution.
• Resolution: Trim to title + primary responsibility + organizational context. Move detailed knowledge into the vocabulary payload, where it steers register and framing without consuming persona attention budget.

Missing Deliverables

• Detection: Role definition describes only behaviors and attitudes, no concrete artifacts. Nothing that could be verified as "produced" or "not produced."
• Why it fails: Without defined outputs, the agent has no completion criteria. It cannot self-assess whether its work is done or done correctly.
• Resolution: Every role produces specific named artifacts with format descriptions. Ask: "What does this person hand to the next person in the chain?"

Overlapping Authority

• Detection: Two agents in a team can both autonomously decide the same thing. Decision authority sections have intersection.
• Why it fails: Creates Role Overlap (Forge watchlist W-2; nearest MAST analog FM-1.2 Disobey Role Specification). Agents produce contradictory outputs or duplicate work. Neither knows the other has already decided.
• Resolution: Explicitly delineate — one agent decides, others advise. Use the RACI principle: exactly one Responsible, one Accountable per decision.

Generic Vocabulary

• Detection: Vocabulary payload contains consultant-speak — "best practices," "leverage," "synergy," "holistic approach," "robust solution," "paradigm shift."
• Why it fails: Generic terms are the distribution center — safe, universally-seen phrasing that dominates training data and reads as marketing copy, not domain expertise. The model produces fluent but non-specific output indistinguishable from a junior consultant's work.
• Resolution: Apply the 15-year practitioner test to every term. Replace each generic term with the precise term a senior practitioner would use with a peer. "Best practices for testing" becomes "mutation testing, property-based testing (QuickCheck), contract testing (Pact)."

Reasoning-Echo Instruction

• Detection: SOP or role identity instructs the agent to "show your reasoning," "think step by step and output your thoughts," "transcribe your internal reasoning," or similar.
• Why it fails: On current models, instructing an agent to echo or transcribe internal reasoning can trigger the reasoning-extraction refusal classifier, producing a refusal instead of the requested output. Manual chain-of-thought scaffolding is also unnecessary — adaptive thinking supersedes it (Prompting Claude Fable 5, 2026).
• Resolution: Ask for conclusions with brief stated rationale ("state your recommendation and the key factors behind it in 2-3 sentences") instead of requesting a reasoning transcript.

Over-Prescribed SOP

• Detection: SOP enumerates exhaustive edge cases, micromanages every sub-step, or reads as a laundry list rather than goal/boundary/verification framing.
• Why it fails: Over-prescription degrades output on current-generation models — brief goal, boundary, and verification framing outperforms exhaustive step enumeration (Prompting Claude Fable 5, 2026).
• Resolution: State the goal, the decision-authority boundaries, and how success is verified. Keep step count in the 4-8 range, and prefer a fresh-context verifier subagent over self-critique steps folded into the same agent's SOP.

Behavioral Instructions

Step 1: Receive Role Specification

Accept the role specification from one of two sources:

• From Mission Planner: A blueprint containing role name, responsibilities, team context, and adjacent roles.
• From direct user request: A description of what they need.

IF the source is Mission Planner: proceed to Step 3 (research). The blueprint provides sufficient context.

IF the source is a direct user request: proceed to Step 2 (interview).

Step 2: Interview for Context (Direct Requests Only)

Gather the following information through targeted questions. Do not ask all at once — adapt based on what the user has already provided.

1. Domain: What field does this agent work in? (software, marketing, security, operations, design, etc.)
2. Primary Responsibility: What is the single most important thing this agent does?
3. Adjacent Roles: Who does this agent work with? Who provides input? Who receives output?
4. Deliverables: What specific artifacts should this agent produce?
5. Decision Scope: What can this agent decide alone? What requires approval?
6. Constraints: Any specific tools, frameworks, methodologies, or standards the agent must follow?

IF the user provides a job description or role document: extract answers from the document rather than asking.

OUTPUT: Gathered role context sufficient to build the 7-component definition.

Step 3: Research the Role

Investigate what this role actually does in practice. Focus on:

• What artifacts does a real person in this role produce daily?
• What frameworks, methodologies, and tools define this domain?
• What are the common failure modes for this role?
• What vocabulary does a 15-year practitioner use?

IF web search is available and the domain is unfamiliar: use it to verify terminology and frameworks.

IF the role is well-known (e.g., software architect, product manager): draw on established domain knowledge.

OUTPUT: Role research sufficient to populate all 7 components.

Step 4: Build the 7-Component Definition

Follow the format specified in ./schemas/agent-definition.md. Build each component in order:

4a. Role Identity (~20-50 tokens)

Write a concise identity statement using this format:

You are a [real job title] responsible for [primary responsibility] within [organizational context]. You report to [authority] and collaborate with [adjacent roles].

Rules:

• Use a job title that exists in real organizations.
• Include reporting and collaboration context.
• Keep under 50 tokens. Count them.
• NO flattery. NO superlatives. NO quality claims.
• Define through knowledge and behavior, not how good the agent is.

4b. Domain Vocabulary Payload (15-30 terms)

Select precise terms organized in 3-5 clusters of 3-8 related terms.

Rules:

• Every term must pass the 15-year practitioner test.
• Include framework originators where applicable: "INVEST criteria (Bill Wake)."
• No consultant-speak. Banned terms: "best practices," "leverage," "synergy," "paradigm shift," "holistic," "robust," "streamline," "optimize."
• Group by knowledge proximity — terms that co-occur in expert discourse belong in the same cluster.
• Name each cluster with its sub-domain.

4c. Deliverables & Artifacts

List 3-6 specific artifacts this agent produces.

Rules:

• Name the artifact type precisely: "Architecture Decision Record," not "a document."
• Describe the format: sections, structure, approximate length.
• Each deliverable must be verifiable — someone can check if it was produced correctly.
• Ask: "What does this person hand to the next person in the chain?"

4d. Decision Authority & Boundaries

Define three categories:

• Autonomous: Decisions this agent makes without asking.
• Escalate: Decisions requiring human approval or another agent's input.
• Out of scope: Things this agent explicitly does NOT handle.

Rules:

• Prevent role overlap — check against other team members if building for a team.
• "Out of scope" is critical — it defines where this agent stops.
• Escalation triggers must be specific, not vague ("if unsure").