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vectr_remember

Store non-obvious code findings, paths, or patterns during development and retrieve them in milliseconds across sessions. Avoid re-reading files with instant semantic recall.

Instructions

Save a working note and recall it on demand in <50ms — whether later this session, through context compaction, or in a future session. Use the moment you discover something non-obvious: a key file path, a call pattern, a gotcha, a partial stub, task progress. Store the actual code or finding — vectr returns it in <50ms; re-reading the file costs tokens and turns. Do NOT store obvious or easily re-derivable facts (e.g. 'the main file is main.py'). Retrieve with vectr_recall(query='what you need') — any time, same session or later.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoMemory kind, controlling how the note is injected (default 'finding'): 'directive' = a must-never-miss rule, injected unconditionally every session; 'task' = current-work context; 'gotcha' = a file/path-anchored caveat; 'finding' = a relevance-ranked learning; 'reference' = a pointer (URL/ticket); 'decision' = an architectural/design decision plus its why — not auto-injected, recall the group chronologically with vectr_recall(kind="decision", sort_by="chronological") for an ADR-style decision history; 'operational' = a build/env/process fact (a build quirk, a CI gotcha, feedback-loop knowledge — e.g. 'tests must run via ./.venv/bin/python'), not anchored to a single code file the way 'gotcha' is. By default surfaces via prompt-time semantic recall (equivalent to declaring triggers=[{'event': 'prompt-submit', 'semantic': True}]). An explicit triggers=[...] REPLACES that default rather than adding to it — declaring triggers=[{'command': '<verb-glob>'}] alone means the note fires ONLY right before a matching shell command and stops firing on prompt-submit. To keep both surfaces, declare both entries: triggers=[{'event': 'prompt-submit', 'semantic': True}, {'command': '<verb-glob>'}]. When a new kind='task' note replaces an earlier checkpoint (the work moved on, the old note is no longer the current state), pass supersedes=<old note_id> so the stale checkpoint stops firing at every future session-start instead of piling up alongside the new one.finding
tagsNoTopic tags for later recall (e.g. ['segment-targeting', 'wip'])
agentNoOptional: your identifier when called by a subagent or orchestrator in a multi-agent workflow (e.g. 'coder-2'). Never inferred — set it explicitly if you want attribution. Shown in vectr_recall() index output as a tag, e.g. '[#12] task/high (coder-2) · title'. A subagent should call vectr_remember with its findings BEFORE finishing so the orchestrator can recall them instead of re-reading the subagent's full transcript.
scopeNoAdvanced: visibility scope, enforced at recall/trigger time. Omit for the kind's own default ('task'→'branch', 'gotcha'→'repo', else 'workspace'); pass explicitly to override — 'branch' (git branch at write time), 'path-subtree' (paths under an anchored dir), 'session' (writing session only), 'repo' (same as 'workspace' today).
titleNoShort label for index-tier display (optional, max ~80 chars). If omitted, the first non-empty line of content is used as the title. Shown in vectr_recall() index output so you can identify notes without reading their bodies.
anchorsNoOptional: file paths this note is about, content-hashed at write time so a later change surfaces as a staleness caveat instead of silently going stale.
contentYesThe note to store. Store whatever you would need to avoid re-reading the file later. If you found a function you'll call or modify — paste its signature and body. If you found a pattern you'll need to replicate — paste the pattern. If you found a location — include the file:line AND the relevant excerpt, not just the pointer. Prose descriptions send the next conversation back to the file; actual code does not.
priorityNoNote priority: 'high' | 'medium' (default) | 'low'medium
triggersNoAdvanced: explicit overrides for WHEN this note resurfaces (path glob, event, symbol, semantic-similarity, timing/cooldown fields — AND within an entry, OR across entries; see docs for the full field DSL). Omit this entirely (recommended) — each kind already gets a sensible default, e.g. 'directive' fires at session-start and after compaction, 'gotcha' fires when its anchored file is about to be edited.
provenanceNoHow much to trust this note when it resurfaces (default 'agent'): 'agent' = self-recorded, framed as memory to verify; 'auto' = no reviewing judgment, weakest framing, incompatible with kind='directive'. 'human' is only reached via explicit promotion, not settable here.agent
supersedesNoOptional: the note_id this new note replaces — the old note is retired (excluded from recall/firing) but kept for audit, unlike vectr_forget. Especially important for kind='task': pass the prior checkpoint's id so it stops firing at every session-start once superseded.
contradictsNoOptional: the note_id this new note proves WRONG — distinct from supersedes (a normal replacement). The target note is revoked: it stays visible on every future recall/fire but rendered as a deterrent ('previously believed... do not re-derive without verification') instead of its raw content, until vectr_reinstate reverses it.
distilled_fromNoOptional: arc ids (from vectr_distill() or GET /v1/arcs) this note distills. After this note is stored, each named arc is marked distilled into it. Unknown/already-resolved ids, and any entry that is not itself an integer, are reported back in the confirmation, never an error and never silently dropped.
Behavior5/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false, which align with the description's write operation. The description adds extensive behavioral context, such as recall speed, default injection behavior based on kind, parameter interactions (e.g., triggers replacing defaults), and special behaviors for supersedes/contradicts. No contradictions.

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 lengthy but well-structured, starting with core purpose, then usage guidelines, and detailed parameter explanations. While every sentence adds value, it could be slightly more concise by externalizing some advanced trigger details. However, given the tool's complexity, the length is appropriate.

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 description covers all aspects of the tool: default behaviors, parameter interactions, edge cases (e.g., triggers replacing defaults, supersedes/contradicts), and usage advice. Despite no output schema, the description provides sufficient context for correct usage. It is complete for a tool with 13 parameters.

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?

Schema coverage is 100%, and the description adds significant meaning beyond schema descriptions. For example, 'kind' explains default behavior and trigger overrides; 'triggers' details default vs explicit usage; 'content' advises on what to store. This helps the agent understand parameter semantics deeply.

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's purpose: 'Save a working note and recall it on demand in <50ms'. It uses specific verbs ('save', 'remember') and resources ('working note'), and distinguishes from sibling tools like vectr_recall (retrieve) and vectr_forget (delete).

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 guidance on when to use the tool ('Use the moment you discover something non-obvious'), what to store ('key file path, call pattern, gotcha, partial stub, task progress'), what not to store ('obvious or easily re-derivable facts'), and references the retrieval tool ('Retrieve with vectr_recall').

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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