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Saaalil
by Saaalil

Load Specialist Context

workforce_as
Read-onlyIdempotent

Loads specialist context for a role, equipping the agent with role-specific skills and defaults, then presents a plan for approval before implementation.

Instructions

Load full specialist context into the agent for a task (skills, stack defaults, quality bars, anti-patterns, handoffs). The agent must investigate the repo, then reply with Goal / Blocking questions (0–3 with defaults) / Assumptions / Plan and stop until approved (unless the change is trivially small). Use when the user says workforce/UI, workforce/DE, DE, Backend, SRE, Ops, etc. This is NOT hiring people — it equips the agent to do that specialty of work at full potential. Short flags: DE UI FE BE DS ML AI ARCH OPS SRE MON SEC QA MGR. Orchestration: workforce_discuss, workforce_delegate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoask (default): investigate then Goal/Blocking questions/Assumptions/Plan and stop; plan: same with a concrete plan; execute: implement after approval
roleYesSpecialist context to load — short flag or full id. Examples: DE, UI, FE, BE, DS, ML, AI, ARCH, OPS, SRE, MON, SEC, QA, MGR or data_engineer, ui_designer, frontend, backend, ops, sre, monitoring, security, qa, manager. Also accepts workforce-DE / workforce/UI / workforce/MGR style strings. This loads agent context for the work — it does not hire people.
taskYesThe work to do under this specialist context
contextNoOptional repo/product/background notes
constraintsNoOptional stack, deadline, brand, compliance, or budget constraints
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only and idempotent behavior, and the description adds process transparency: the agent must investigate the repo, reply with Goal/Blocking questions/Assumptions/Plan, and stop until approved (unless trivially small). This goes beyond the annotations by disclosing the expected workflow and stopping condition.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main purpose and immediately explains key behavior, then usage, clarifications, and flags. It is dense but every sentence serves a purpose; a minor deduction for slightly packed phrasing that could be streamlined without losing information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema, the description sufficiently explains what the agent should return (Goal/Blocking questions/Assumptions/Plan). It also covers triggers, exclusions, role flag syntax, and orchestration context, making the tool's behavior complete for an agent to select and invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already covers all parameters with descriptions (100% coverage), so baseline is 3. The description adds value by listing short flags (DE, UI, FE, etc.), clarifying that the role parameter loads context rather than hiring, and implicitly explaining the mode behavior through the overall process description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb+resource pair ('Load full specialist context into the agent for a task') and enumerates what the context contains (skills, stack defaults, quality bars, anti-patterns, handoffs). It also differentiates from siblings by explicitly stating 'This is NOT hiring people' and referencing orchestration tools, making its unique role clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit trigger phrases ('Use when the user says workforce/UI, workforce/DE, DE, Backend, SRE, Ops, etc.'), an exclusion ('This is NOT hiring people'), and points to related tools for orchestration (workforce_discuss, workforce_delegate). This gives clear when-to-use and when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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