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dialectforge

FlowState by DialectForge

Official

attempt

Destructive

Log and track solution attempts for projects, recording outcomes like success or failure to build shared memory across AI apps.

Instructions

Manage solution attempts. Actions: log, outcome Write: requires project="" (or project_id).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoYour model name, if you know it (optional; never guessed)
notesNo
actionYes
outcomeNo
projectNoProject name or id. Required for every write.
attempt_idNo
confidenceNoattempted
problem_idNo
descriptionNo
parent_attempt_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.4/5.0
Behavior2/5

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

Annotations declare destructiveHint=true and readOnlyHint=false, so the agent knows writes occur, but the description never discloses what an outcome write changes, whether it overwrites prior attempt state, or what parent_attempt_id relationships imply. It adds the project prerequisite, which is useful, but for a destructive multi-action tool with no consequences explained, disclosure is thin.

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

Conciseness3/5

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

Two short sentences, front-loaded with the resource and the action list, so it is easy to scan and wastes no words. But the brevity is under-specification rather than efficient density, leaving the reader with almost nothing actionable for a 10-parameter tool.

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

Completeness2/5

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

For a destructive, two-action tool with 10 parameters, 20% schema coverage, and no output schema, the description is far too sparse. It should at minimum explain what each action writes, how outcome/confidence relate, and what the required project scoping implies. Key call-correctness information is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 20% (10 parameters), so the description must compensate, and it does not. It mentions the project requirement (already in the schema) but leaves action semantics, outcome values, confidence levels, attempt_id, problem_id, and parent_attempt_id unexplained. Most parameters are undocumented in both places.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the resource ('solution attempts') and lists the two actions (log, outcome), which gives some shape to an otherwise opaque tool name. However, 'Manage' is a vague verb that does not say what logging or setting an outcome actually accomplishes, and it does not differentiate this from siblings like 'problem', 'verify', or 'log_work'. An agent knows the domain but not the concrete operation.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives such as 'problem', 'log_work', or 'verify', nor when to choose action='log' over action='outcome'. The only conditional given ('Write: requires project=...') is a prerequisite, not usage routing. The agent must infer the workflow entirely.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.