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dihannahdi

Mycelium

by dihannahdi

mycelium_zoom

Zoom into a data entity to inspect it at forest, tree, or leaf level. Defaults to tree; leaf reveals full column names and query patterns. Manages working memory by limiting leaf resolution to four entities.

Instructions

Materialise one entity at a chosen level of detail, and admit it to working memory.

Default to tree. Go to leaf only when you need column names, real query patterns, or assertion detail -- that is, when you are about to write SQL or name a specific field.

At most four entities sit at leaf resolution at once. If you need a fifth, the least-used one is demoted to make room; that is the mechanism working, not a failure. If the response says columns were truncated, quote the stated count rather than concluding a column is absent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urnYesThe entity to look at more closely.
levelNo'forest' (it exists), 'tree' (identity + relations), 'leaf' (full).tree

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description fully shoulders the burden. It discloses the demotion policy for leaf entities and warns about column truncation, advising to quote the count rather than assume absence.

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 concise, front-loaded with the core purpose, followed by usage guidelines and behavioral notes. Every sentence earns its place without redundancy.

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?

Covering purpose, usage, behavior, and parameters, and given the presence of an output schema, the description is complete and self-sufficient for correct tool selection and invocation.

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

Parameters5/5

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

The description enriches the schema by explaining the three levels ('forest', 'tree', 'leaf') with practical usage contexts, and notes the default. This goes beyond the schema's brief descriptions.

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 materializes an entity at a chosen level of detail and admits it to working memory. It distinguishes this from other mycelium tools (e.g., mycelium_ask, mycelium_forage) by focusing on zooming into a single entity.

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?

Explicit guidance is provided: default to 'tree', use 'leaf' only when column names or query patterns are needed (e.g., before writing SQL). It also notes the constraint of at most four leaf entities, explaining the demotion mechanism.

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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