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memory_store

Store one atomic fact to long-term memory, enabling future sessions to recall it. Automatically deduplicates and surfaces conflicts.

Instructions

Persist one atomic fact to long-term memory. Call this whenever you learn something a future session would need: a service detail, a decision rationale, a workaround, a user preference, an ownership fact, a task-resume pointer. One fact per call — split compound observations into separate calls. Dedup is automatic (content hash + vector similarity), so you do NOT need to recall first for deduplication. Recall first only when you intentionally need broader context to decide whether a new fact supersedes an older one. The tool returns one of: inserted (new fact), reinforced (exact or near-duplicate found — counters bumped), or — if there are similar-but-different facts — a list of potential conflicts so you can decide whether to use 'supersedes'. To create a typed edge between two entities at the same time, set the optional 'relation' field — no separate tool call needed. Do NOT use for ephemeral state (current cursor, in-flight todo). Use the harness task folder instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoKnowledge form of the memory object. One of: • fact — Atomic, durable memory that should be retrievable independently. • summary — Compressed representation of a session index, coherent episode, or current workstream state. • distilled — Convention or reusable learning synthesized from multiple memories. • relation — Typed edge between entities; relation_type carries the edge label. Default when omitted: fact. (telemetry is reserved for the daemon.)fact
repoNoRepository or project surface this fact relates to (e.g. 'bikky-dev/bikky').
branchNoBranch or working surface (e.g. 'main', 'feat/x').
domainNoActivity profile that controls vocabulary and ranking. One of: • software_engineering — Coding-agent work: repositories, code changes, architecture, infrastructure, debugging, tests, CI, and developer workflow. • product_strategy — Product direction, positioning, roadmap tradeoffs, customer problems, metrics, and market learning. • business_operations — Business process, vendors, finance, legal/admin operations, recurring procedures, and ownership. • research — Research questions, sources, hypotheses, experiment findings, synthesis, and reusable insights. • personal_productivity — Individual productivity, habits, planning preferences, reminders, and personal operating context. Default when omitted: software_engineering.software_engineering
contentYesThe fact to store. Should be one atomic, self-contained statement (no compound 'A and B') that makes sense out of context.
categoryYesSubject matter of the fact. One of: • engineering — Engineering context: codebase maps, architecture decisions, infrastructure topology, access patterns, operations, troubleshooting, and reusable conventions. • product — Product context: domain rules, product decisions, requirements, user workflows, roadmap, success metrics, and market or community insight. • system — System context: Bikky-owned lifecycle memory, session indexes, episodes, workstreams, recall/feedback/outcome telemetry, and aggregate rollups. Default when omitted: engineering.
entitiesYesLowercase entity names mentioned by this fact (e.g. ['qdrant', 'workspace_id']). Used for entity-scoped recall and graph traversal — keep them short and canonical.
metadataNoArbitrary key-value metadata. Stored with the fact and exact-match filterable via memory_recall.metadata_filter (all key/value pairs must match — AND logic).
relationNoOptional typed edge between two entities — created in the same call. Use this whenever the fact also expresses a relationship; no separate tool call needed.
task_keyNoTask or issue key (e.g. GitHub issue number, JIRA key).
confidenceNoHow certain you are this fact is correct (0.0-1.0). Default 0.9. Lower (~0.6) for inferred or unverified facts.
episode_idNoCoherent activity-segment ID. Group facts captured during the same coherent task or transcript.
importanceNoHow important this fact is for future recall (0.0-1.0). Defaults to 0.5 if omitted. ≥0.8 surfaces in session briefings.
supersedesNoID of an existing fact that this one replaces. The old fact is marked superseded and excluded from recall. Use this when a fact is updated; use memory_forget when a fact was simply wrong.
destinationNoOptional destination override. When set, routes to that destination by name. Hard-errors if no such destination exists. Omit to let routing rules in ~/.bikky/config.json decide based on cwd/entities/content/metadata.
workspace_idNo[Removed in v0.4.0] No-op. Routing now uses destinations — see destination.
review_statusNoReview lifecycle status. candidate=auto-extracted (daemon), reviewed=human-checked, approved=human-confirmed, rejected=incorrect. Agents normally leave this unset.
memory_subtypeNoOptional finer-grained type within the kind. Only set when one of these clearly applies — otherwise leave blank. Subtype must match the kind (validated server-side): • kind=fact: codebase_map, architecture_decision, infra_topology, access_pattern, operational_procedure, domain_rule, product_decision, product_requirement, user_workflow, roadmap_item, success_metric, market_insight, troubleshooting_gotcha, preference, person_profile, ownership_note, working_agreement, activity_event • kind=summary: session_index, episode, workstream • kind=distilled: convention • kind=telemetry: recall_event, feedback_event, outcome_event, aggregate_rollup
workstream_keyNoDurable continuity key for a long-running objective (survives across sessions).
Behavior5/5

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

No annotations are provided, so the description fully covers behavioral traits. It explains return values (inserted, reinforced, potential conflicts), dedup mechanism, and the supersedes workflow. It also clarifies that relation edges can be created in the same call.

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

Conciseness4/5

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

The description is well-structured and front-loaded with the purpose. It contains several sentences, but every sentence adds value. Slightly verbose but still clear and organized.

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?

The tool has 19 parameters (3 required) and no output schema, yet the description covers return types, dedup, relation creation, and exclusions. It provides a comprehensive guide for this complex write tool.

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 the schema already documents all parameters. The description adds usage context beyond the schema, such as the dedup behavior, one-fact-per-call rule, and how to use the relation field. This adds significant value beyond 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 'Persist one atomic fact to long-term memory' and distinguishes this tool from siblings like memory_recall and memory_forget. It specifies the verb (persist), resource (memory), and scope (one atomic fact).

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 provides explicit when-to-use guidance (learning something future sessions need) and when-not-to-use (ephemeral state). It explains dedup behavior and directs users to recall first when broader context is needed. Alternatives like harness task folder 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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