Skip to main content
Glama

capture_lesson

Document lessons learned by providing details manually, extracting them from text automatically, or searching existing lessons by keyword.

Instructions

Capture lessons: inline / batch write, or lookup by keyword.

Inline mode (default): provide title, context, problem, solution. Batch mode: provide text to extract lessons automatically via worker. Lookup mode: provide find to surface top-ranked existing lessons whose heading matches the keyword.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectYesProject slug (directory under 10_projects/).
titleNoShort descriptive title (inline mode).
contextNoWhat you were doing (inline mode).
problemNoWhat went wrong or what decision was needed (inline mode).
solutionNoWhat fixed it or what was decided (inline mode).
tagsNoOptional tags (e.g. ["python", "testing"]).
textNoRaw text to extract lessons from (batch mode).
min_confidenceNoMinimum confidence for batch extraction. Default 0.7.
max_lessonsNoMaximum lessons to extract / surface. Default 5.
findNoKeyword to look up in existing lesson headings (lookup mode).
rank_byNoLookup ranking — 'reinforcements' (default), 'confidence', or 'hybrid'. Ignored unless ``find`` is set.reinforcements

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations indicate readOnlyHint=false, confirming it's a write tool. The description reinforces this by using 'capture' and details each mode's behavior (inline, batch, lookup). No contradicting information.

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: a single opening line followed by three mode descriptions. Each sentence serves a purpose and information is front-loaded.

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?

Despite 11 parameters and 1 required, the description covers all modes and parameter usage. An output schema exists, so return values need not be explained. The description is complete for effective tool usage.

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%, so baseline is 3. The description adds value by grouping parameters under modes (e.g., 'Inline mode: provide title, context, problem, solution') and specifying defaults and behavior (e.g., 'Ignored unless find is set'). This surpasses the baseline.

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 captures lessons and explicitly lists three modes (inline, batch, lookup) with distinct actions. It differentiates from sibling tools which focus on vault operations and task delegation.

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?

The description explains when to use each mode: inline for direct entry, batch for automatic extraction, lookup for searching. This provides clear context and guidance without needing to mention exclusions since modes are self-explanatory.

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/mlorentedev/hive'

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