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configure_tracing

Set trace mode to 'full' or 'safe' and toggle live reasoning streaming, with settings persisted across sessions. Changes take effect on the next call—no restart or config file edit needed.

Instructions

Toggle reasoning-trace capture at runtime, persisted across sessions (writes ask_fable's config file, which overrides the ASK_FABLE_TRACE_MODE / ASK_FABLE_STREAM_REASONING env defaults — no ~/.claude.json edit or restart needed; it applies on the next call). trace_mode='full' records redacted model reasoning into traces and trace bundles (and saves answer markdown); 'safe' withholds reasoning content while structural traces still record. stream_reasoning=true|false turns live thinking on the server console on or off. Pass either or both. Returns the effective settings and the config path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trace_modeNo'full' captures redacted model reasoning into traces and trace bundles (and saves answer markdown); 'safe' withholds reasoning content while structural traces still record. Persisted; overrides ASK_FABLE_TRACE_MODE. Takes effect on the next call — no restart.
stream_reasoningNoStream model thinking live to the ask_fable console as calls run (true) or off (false). Persisted; overrides ASK_FABLE_STREAM_REASONING. Streams to the server's own console, not into this tool result.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.12.0

TDQS

A4.1/5.0
Behavior5/5

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

With no annotations provided, the description carries full disclosure burden and succeeds. It reveals the side effect of writing ask_fable's config file, persistence across sessions, overrides of environment defaults, the fact that changes apply on the next call, and the behavioral difference between 'full' and 'safe' trace modes. It also discloses that stream_reasoning goes to the server console rather than the tool result.

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 definition is information-dense and front-loaded with the core action in the first phrase. Each clause adds useful detail, but the opening sentence is long and packs multiple ideas (persistence, config file override, no restart, next-call timing) into one parenthetical-heavy statement. Still, nothing is wasted.

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?

For a config-mutation tool with no annotations and no output schema, the description is remarkably complete. It explains persistence, override behavior, timing, both modes for trace_mode, the effect of stream_reasoning, and explicitly states the return value (effective settings and config path). An agent has enough to use it correctly.

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 baseline is 3. The description repeats and slightly expands on the schema's parameter descriptions (e.g., 'full' records redacted reasoning, 'safe' withholds content), but does not add substantially new semantic meaning beyond what the input schema already states.

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

Purpose4/5

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

The description starts with a specific verb+resource: 'Toggle reasoning-trace capture at runtime', which clearly states the action and target. It clarifies what the tool is for, but does not explicitly contrast itself with sibling tools like trace_get or trace_list, so it misses the top bar for sibling differentiation.

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 gives clear context: it is a runtime toggle that persists, overrides env defaults, requires no ~/.claude.json edit or restart, and applies on the next call. It also says 'Pass either or both' to guide invocation. It does not explicitly state when to prefer this over read-only trace tools, so it stops short of full when/when-not guidance.

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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