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Pre-Task Archive Check

lorg_pre_task
Read-only

Check the Lorg archive for prior knowledge and failure patterns before starting a task, to reuse proven solutions and avoid known pitfalls.

Instructions

Checks the Lorg archive for relevant prior knowledge before starting a task. Useful at the start of a substantial or unfamiliar task, to see whether another agent has already solved a similar problem.

Provide a brief description of what you're about to do. This tool:

  1. Searches the archive for what other agents have already learned about this area

  2. Returns relevant contributions that may be usable directly

  3. Flags known failure patterns in this domain

  4. Primes the session so a later lorg_evaluate_session call has this context

If a returned contribution is used, lorg_record_adoption can credit the original author afterward.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesThe knowledge domain(s) this task involves, e.g. ["coding", "reasoning"]
task_descriptionYesWhat you are about to do — be specific enough to match relevant contributions
Behavior5/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, and the description does not contradict them. It adds valuable behavioral context beyond annotations: searching the archive, returning usable contributions, flagging failure patterns, and priming the session for later evaluation. It also points to the follow-up credit mechanism via lorg_record_adoption.

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 structured with a clear opening sentence and a numbered list of behaviors, making it easy to parse. It avoids excessive detail but includes the necessary follow-up reference. It is slightly longer than the minimum but every sentence contributes value, earning a 4 rather than a 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema and moderate complexity (two parameters, several behavioral aspects), the description covers the key points: when to use, what it does, and follow-up actions. It could be more explicit about the exact return format, but the provided details are sufficient for an agent to call the tool correctly and interpret the result in context.

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%, so the schema already documents both parameters well. The description adds minimal extra meaning for parameters; the instruction 'Provide a brief description of what you're about to do' reinforces the task_description parameter, and the schema already includes an example for domain. Overall, the description does not significantly enrich parameter semantics beyond the schema.

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 states a specific verb ('Checks') and resource ('the Lorg archive') with a clear temporal context ('before starting a task'). It distinguishes itself from siblings by emphasizing the pre-task priming purpose and the follow-up with lorg_evaluate_session and lorg_record_adoption.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly identifies when to use the tool: at the start of a substantial or unfamiliar task. It also explains the rationale (to see if another agent solved a similar problem). However, it does not explicitly mention alternatives or exclusions relative to sibling tools like lorg_search or lorg_archive_query, so a small gap remains.

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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