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save_conversation

Save complete conversations as searchable memories with automatic context extraction and project tracking. Updates existing memories or creates new ones.

Instructions

Save complete conversations as memory. REQUIRED: Send COMPLETE conversation in 'conversationContent' parameter (minimum 100 chars, should be thousands). Include EVERY message verbatim - NO summaries or partial content.

Intelligently tracks context, extracts project details, and routes to a single memory per conversation topic.

HOW SAVES TARGET MEMORIES:
- conversationId is auto-generated from title slug (e.g., "MCP Tools" → "mcp-tools")
- Same title (or explicit conversationId) → targets the existing memory
- The 'mode' parameter controls what happens to that existing memory:
  • mode='replace' (default): overwrites the existing content with what you send
  • mode='append': concatenates new content below existing with a timestamped separator
    (\n\n--- UPDATE <ISO8601> ---\n\n) — preserves all prior history in the live row
- The /save skill sets mode='append' automatically for living-document use
- For one-shot snapshots, ad-hoc captures, or explicit overwrite: pass mode='replace'

PRIOR CONTENT IS NEVER LOST:
- Even with mode='replace', prior content is snapshotted to memory_events audit log on every update
- Recovery from overwrites requires a one-off script (out-of-band)
- Use mode='append' if you want history to remain visible inline in the live memory

INTELLIGENT EXTRACTION (independent of mode):
- Auto-extracts project context (name, component, feature being discussed)
- Detects work iteration and status (planning/in_progress/completed/blocked)
- Generates smart titles like "Purmemo - Timeline View - Implementation"
- Tracks technologies, tools used, identifies relationships/dependencies

SERVER AUTO-CHUNKING:
- Large conversations (>15K chars) automatically split into linked chunks
- Small conversations (<15K chars) saved directly as single memory
- You always send complete content — server handles chunking
- APPEND + CHUNKING: append mode works only for content <15K chars. Saves >15K
  with mode='append' are rejected with a clear error — appending to chunked
  storage would double each chunk's content on re-save. For long-running living
  docs, send only the new delta since the last save (keep it <15K) or use
  mode='replace' for full re-saves.
- KNOWN CAVEAT: a doc that is saved small (single memory) and later grows past 15K
  transitions to chunked storage at a new conversation_id space — the original
  single memory becomes orphaned. Tracked under ADR-038 (uniform namespace).

EXAMPLES:
User: "Save progress" via /save skill
→ /save sets mode='append'; new content is appended below prior content

User: "Save this snapshot" (one-shot capture)
→ mode='replace' default; current content overwrites any existing memory at this title

User: "Save as conversation react-hooks-guide" with explicit append
→ save_conversation(conversationId="react-hooks-guide", mode="append")
→ Appends to existing memory at that ID (or creates if new)

WHAT TO INCLUDE (COMPLETE CONVERSATION REQUIRED):
- EVERY user message (verbatim, not paraphrased)
- EVERY assistant response (complete, not summarized)
- ALL code blocks with full syntax
- ALL artifacts with complete content (not just titles/descriptions)
- ALL file paths, URLs, and references mentioned
- ALL system messages and tool outputs
- EXACT conversation flow and context
- Minimum 500 characters expected - should be THOUSANDS of characters

FORMAT REQUIRED:
=== CONVERSATION START ===
[timestamp] USER: [complete user message 1]
[timestamp] ASSISTANT: [complete assistant response 1]
[timestamp] USER: [complete user message 2]
[timestamp] ASSISTANT: [complete assistant response 2]
... [continue for ALL exchanges]
=== ARTIFACTS ===
[Include ALL artifacts with full content]
=== CODE BLOCKS ===
[Include ALL code with syntax highlighting]
=== END ===

IMPORTANT: Do NOT send just "save this conversation" or summaries. If you send less than 500 chars, you're doing it wrong. Include the COMPLETE conversation with all details.

ARTIFACT PRESERVATION (ADR-025):
If this conversation produced artifacts (research reports, tables, frameworks, specs, design documents),
save them SEPARATELY using save_artifact after this call.
Flow: save_conversation first, then save_artifact for each artifact.
This ensures artifacts are preserved in full — do not try to embed large artifacts in conversationContent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conversationContentYesCOMPLETE conversation transcript - minimum 500 characters expected. Include EVERYTHING discussed.
titleNoTitle for this conversation memoryConversation 2026-06-21T14:08:37.634Z
conversationIdNoOptional unique identifier for living document pattern. If provided and memory exists with this conversationId, UPDATES that memory instead of creating new one. Use for maintaining single memory per conversation that updates over time.
tagsNoTags for categorization
priorityNoPriority level for this memorymedium
modeNoHow to handle a save that targets an existing memory (same title or conversationId). "replace" (default) overwrites the existing content with what you send. "append" concatenates new content below the existing content with a timestamped separator (\n\n--- UPDATE <ISO8601> ---\n\n). Use "append" for living documents you genuinely want to grow over time; use "replace" for one-shot snapshots and ad-hoc captures. The /save skill defaults to "append" automatically — you only need to pass this for explicit overrides.replace
Behavior5/5

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

The description extensively discloses behavioral traits beyond annotations: auto-generation of conversationId, mode behavior (replace/append), snapshotting to audit log, chunking rules, known caveat about orphaned memories. It doesn't contradict annotations (readOnlyHint=false is consistent with write operation).

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 long but well-structured with clear sections, tables, and examples. Every sentence adds value, covering edge cases and caveats. Could be slightly trimmed but remains efficient for the complexity.

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 is complete for a complex write tool with 6 parameters and no output schema. It covers content requirements, chunking behavior, mode interactions, artifact preservation workflow, and known limitations. No gaps remain for an agent to misuse the tool.

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 value for each parameter: explains auto-generation of conversationId, mode control with examples, content formatting requirements, and priority usage. The mode parameter is elaborated far beyond schema enum values.

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 'Save complete conversations as memory' and specifies the verb 'save' with a defined resource 'conversation'. It differentiates from sibling tool 'save_artifact' by explicitly telling when to use each, and from other tools like 'commit' or 'save_snapshot' by focusing on conversation memory.

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 gives explicit when-to-use guidance: 'Save complete conversations as memory' with REQUIRED flag. It also says when not to use: avoid embedding large artifacts, use 'save_artifact' separately. It explains the '/save' skill default behavior and when to override mode. Provides flow: save_conversation first, then save_artifact.

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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