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store_knowledge_memory

Store knowledge entities with type, description, and metadata into a graph for semantic search and linking. Capture insights, patterns, and decisions to build a searchable knowledge base.

Instructions

Store a knowledge graph memory with entity creation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repository_pathYesThe absolute path to the repository where the knowledge entity should be stored
agent_idYesThe ID of the agent storing this knowledge entity
entity_typeYesThe type of entity being stored (e.g., 'function', 'class', 'concept', 'file', 'bug', 'feature', 'person', 'organization', 'technology', 'pattern', 'insight', 'question', 'decision', 'requirement', 'test', 'documentation', 'api', 'database', 'configuration', 'deployment', 'performance', 'security', 'error', 'warning', 'todo', 'note', 'example', 'tutorial', 'best_practice', 'anti_pattern', 'code_smell', 'refactor', 'optimization', 'dependency', 'service', 'component', 'module', 'library', 'framework', 'tool', 'script', 'command', 'variable', 'constant', 'enum', 'interface', 'type', 'schema', 'model', 'view', 'controller', 'route', 'middleware', 'plugin', 'extension', 'theme', 'style', 'asset', 'resource', 'data', 'event', 'listener', 'handler', 'callback', 'promise', 'async', 'sync', 'thread', 'process', 'memory', 'storage', 'cache', 'session', 'cookie', 'token', 'auth', 'permission', 'role', 'user', 'group', 'setting', 'config', 'env', 'flag', 'feature_flag', 'experiment', 'metric', 'log', 'trace', 'debug', 'info', 'warn', 'error', 'fatal', 'success', 'failure', 'retry', 'timeout', 'rate_limit', 'quota', 'limit', 'threshold', 'rule', 'policy', 'standard', 'guideline', 'convention', 'protocol', 'format', 'encoding', 'compression', 'encryption', 'hash', 'checksum', 'signature', 'certificate', 'key', 'secret', 'password', 'credential', 'identity', 'profile', 'account', 'subscription', 'plan', 'tier', 'level', 'rank', 'score', 'rating', 'review', 'feedback', 'comment', 'message', 'notification', 'alert', 'reminder', 'task', 'job', 'queue', 'batch', 'stream', 'pipeline', 'workflow', 'process', 'procedure', 'method', 'algorithm', 'structure', 'pattern', 'template', 'prototype', 'mock', 'stub', 'fake', 'spy', 'double', 'fixture', 'seed', 'migration', 'rollback', 'upgrade', 'downgrade', 'patch', 'hotfix', 'release', 'version', 'branch', 'tag', 'commit', 'merge', 'rebase', 'cherry_pick', 'stash', 'diff', 'conflict', 'resolution', 'other')
entity_nameYesThe name or identifier of the knowledge entity
entity_descriptionNoA detailed description of the knowledge entity and its purpose
importance_scoreNoThe importance score of this entity (0.0 to 1.0, where 1.0 is most important)
confidence_scoreNoThe confidence score for this entity's accuracy (0.0 to 1.0, where 1.0 is most confident)
propertiesNoAdditional properties and metadata for the entity as key-value pairs
Behavior3/5

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

No annotations exist, so the description must carry the burden. It mentions that the entity will be stored with vector embeddings for semantic search, which adds useful context. However, it does not disclose side effects, authorization requirements, or error conditions.

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

Conciseness2/5

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

The description is a single short sentence that barely adds value beyond the tool name. While concise, it is under-informative and does not earn its place given the tool's complexity. The input schema's embedded description provides more detail, but the primary description is lacking.

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

Completeness2/5

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

With 8 parameters, no output schema, and nested objects, the tool is moderately complex. The description fails to cover usage context, return behavior, or integration with other knowledge graph tools. It is insufficient for an agent to use correctly without additional schema details.

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?

Schema description coverage is 100%, so the schema already documents all parameters. The description adds no additional parameter-level meaning beyond the overall purpose. Baseline 3 is appropriate.

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

Purpose4/5

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

The description clearly states it stores a knowledge graph memory by creating an entity. It is specific enough to distinguish from sibling tools like search_knowledge_graph or create_knowledge_relationship, though it does not explicitly differentiate them.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. The description says 'Use this to capture important information' but lacks exclusions or context about when not to use it. No alternative tools are mentioned.

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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