Skip to main content
Glama

get_supportive_context

Read-onlyIdempotent

Load supportive context reference documents for project variants to guide workflow, routing, and edge cases. Retrieve on demand to refresh stale information.

Instructions

Returns supportive context reference documents by variant. All variants auto-provided: core + coding by aimfp_run(is_new_session=true) for initialized projects, case2 by aimfp_run when Case 2 active, init by aimfp_init(). Also callable on demand to reload stale context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
variantNoWhich context to load: 'core' (workflow, routing, edge cases — default), 'init' (discovery depth, initialization), 'coding' (file loop, DRY, interactions, types), 'case2' (Use Case 2 pipeline)core
Behavior3/5

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

Annotations already declare readOnlyHint and idempotentHint, indicating a safe, idempotent read operation. The description adds value by explaining the auto-provisioning behavior and the fact that it returns reference documents, but does not disclose additional behavioral traits beyond what annotations imply.

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

Conciseness5/5

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

The description is extremely concise: two sentences that pack the core purpose and behavioral details without any fluff or repetition. Every sentence serves a purpose.

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

Completeness4/5

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

Given the tool has one parameter, no output schema, and comprehensive annotations, the description is largely complete. It explains all variants and when they are auto-provided. It could optionally detail the return format (e.g., 'list of document strings') but the absence is minor for a simple retrieval tool.

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

Parameters3/5

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

The input schema provides 100% coverage for the single parameter 'variant', including a description and default value. The tool description mentions variants but does not add new semantic information or format details beyond what is already in the schema's parameter description. Baseline 3 is appropriate.

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 clearly states the tool returns supportive context reference documents by variant, and enumerates the available variants (core, coding, case2, init). This specific verb+resource combination distinguishes it from numerous sibling get_* tools.

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

Usage Guidelines4/5

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

The description explains when variants are auto-provided (e.g., core and coding via aimfp_run with is_new_session=true, case2 when active, init via aimfp_init()) and mentions it is callable on demand to reload stale context. It gives clear context for usage but does not explicitly state when not to use it or mention alternatives.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/aryanduntley/aimfp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server