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td_knowledge_save

Save free-form markdown knowledge entries like essays, notes, or explanations. Stores them locally with metadata for later retrieval.

Instructions

Persist a free-form markdown knowledge entry (prose/notes/essays).

Returns the entry id. The body is stored at ~/.tdpilot/knowledge//entries/.md and the metadata in index.json. Local-only, never pushed anywhere. Prefer td_memory_save (with td_memory_learn) when you want to capture a structured, replayable technique recipe rather than free-form prose.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesMarkdown body of the knowledge entry. Reference essay, math, explanations — keep under 200 KB. Split larger writeups into multiple linked entries.
nameNoShort title for the entry.
tagsNoLowercase tags for filtering, e.g. ['feedback', 'reaction-diffusion'].
notesNoFree-form internal notes.
scopeNo'project' or 'global'. Project requires TDPILOT_PROJECT_NAME.project
sourceNoOptional attribution — where this technique came from (e.g. 'youtube tutorial 2025-03-01', 'forum post').
descriptionNoOne-line summary used in search results.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Describes return value ('Returns the entry id'), exact file storage paths, and scope constraints ('Local-only, never pushed anywhere'). Annotations only show readOnlyHint=false, description adds crucial behavioral details without contradiction.

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?

Three efficient sentences: purpose, storage behavior, usage alternative. No wasted words, front-loaded with core action.

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?

Covers purpose, return, storage, constraints, and sibling guidance. Output schema exists so return details are covered. Could mention idempotency or side effects, but not required for completeness given annotations.

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?

Schema coverage is 100%, description adds value for 'body' parameter (reference content, size limit, splitting advice). Other parameters have schema descriptions that suffice; description doesn't need to duplicate.

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?

Description clearly states 'Persist a free-form markdown knowledge entry' with verb+resource+format, and explicitly distinguishes from sibling td_memory_save by contrasting structured recipes vs free-form prose.

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?

Explicitly states when to prefer td_memory_save instead, and gives constraints like 'keep under 200 KB' and 'split larger writeups'. Lacks explicit 'when not to use' but alternative is clearly identified.

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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