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Load a token-budgeted resume of Agentpack task state to orient at startup: Task Passport, git state, decisions, dead ends, and gate warnings before reading code.

Instructions

Load a token-budgeted markdown resume of Agentpack state for the current task: Task Passport status and next actions, git state, query-relevant decisions, dead ends, and source conclusions, plus gate warnings when the task lifecycle needs attention. Call once at the start of a session or task, before reading code; re-call only for a different query or budget. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoFocused free-text query for the current task. Matching source records keep full summaries; unrelated records collapse to compact stubs to save tokens.
budgetNoApproximate token budget for the resume. Takes precedence over preset. Default 4000.
presetNoNamed token budget: quick (1200), chat (4000), agent (8000), or deep (16000). Use quick for task-start orientation.
Behavior4/5

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

Annotations declare readOnlyHint=true, and the description adds 'Read-only' while also revealing token-budgeting behavior and the presence of gate warnings. This goes beyond the annotation by explaining what the resume includes and how the tool handles queries, though the exact output format is not specified.

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

Conciseness5/5

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

The description is concise yet information-dense, using three sentences to convey the core function, usage frequency, and safety note. Each clause contributes value, and key facts are front-loaded in the first sentence.

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?

With read-only annotations and a fully described schema, the description explains what the resume contains (status, git, decisions, dead ends, conclusions) and when to call/re-call. Although there is no output schema, the content outline is sufficient for an agent to understand the tool's behavior and expected output.

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 coverage is 100% with detailed param descriptions for query, budget, and preset. The description only references 'query or budget' in usage guidance without adding new semantic detail, so the baseline score of 3 applies as the schema carries the heavy lifting.

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 loads a token-budgeted markdown resume of Agentpack state, enumerating specific content like Task Passport status, git state, decisions, and gate warnings. This distinguishes it from sibling tools by its start-of-session context-loading purpose and explicit resource scope.

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 usage guidance: 'Call once at the start of a session or task, before reading code; re-call only for a different query or budget.' This establishes when to use the tool, when not to re-call, and the rationale for doing so, though no alternative tool names 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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