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get_agent_bootstrap

Bootstrap an AI agent's session in one call by returning architecture, hot symbols, last focus, user framing, error patterns, and recent timeline. Replaces a four-call sequence to avoid starting from scratch.

Instructions

Single-call session bootstrap for AI agents. Replaces the 4-call sequence (get_session_brief → get_last_context → get_user_profile → get_error_patterns) with one ~300-token payload.

Returns: repo — project name architecture — 600-char architecture summary hot_symbols — ["fn:file:line", ...] top 8 symbols by behaviour weight last_focus — {files, query, agent} from last agent's context_pack framing — {depth, vocabulary} from user profile (empty if tracking off) error_patterns — top 3 recurring errors with prevention hints index_health — {symbols, files, status} recent_timeline — last 5 entries (past 7 days) merged across sessions, episodes, decisions, and errors — {ts, kind, summary, ref} each; see data/memory/timeline.py::merge() for the full query surface (since/include_archived/limit)

Claude: call this ONCE at session start instead of the 4 individual calls. Use individual tools only when you need the full detail each provides.

repo_path: optional absolute path to the target repository.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repo_pathNo
Behavior4/5

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

With no annotations, the description carries the transparency burden. It discloses the combined nature of the payload, mentions that framing may be empty if tracking is off, and explains the merged timeline. It doesn't explicitly state it's read-only, but the content implies it. A bit more detail on side effects or costs would elevate it to 5.

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 with a clear first sentence, a bulleted return list, and a usage note. It is longer than the minimum but every part contributes. The reference to 'data/memory/timeline.py::merge()' is slightly over-specified for a typical agent, but the overall formatting is efficient.

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?

Given no output schema, the description thoroughly explains the return shape, including types and examples for each field. It also covers the parameter, alternatives, and usage context. The description is complete for an agent to decide and invoke the tool without further ambiguity.

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?

The only parameter, repo_path, is explained as 'optional absolute path to the target repository.' This adds meaning beyond the schema's anyOf/null/default. It doesn't specify default behavior, but the optionality is clear. For a single parameter, this is adequate.

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: a single-call session bootstrap for AI agents. It explicitly names the four calls it replaces (get_session_brief, get_last_context, get_user_profile, get_error_patterns), making it distinct from siblings.

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?

Provides explicit usage instructions: 'call this ONCE at session start instead of the 4 individual calls' and 'Use individual tools only when you need the full detail each provides.' This clearly delineates when to use this tool vs alternatives.

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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