Skip to main content
Glama

financial_setback_processing

Process financial setbacks from market losses, drawdowns, or allocation regrets using a deterministic playbook. Provides structured recovery guidance.

Instructions

Domain-specific recovery for trading/portfolio/financial setbacks (market loss, position drawdown, allocation regret). Deterministic playbook. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
loss_usdNoOptional: absolute loss in USD
session_idYesYour active session ID
asset_classNoOptional: equities | crypto | bonds | options | other
ritual_stripNoOptional machine hygiene flag. When true, returns structured output without ritual/narrative prose, model-safe preambles, or guardrail alias blocks.
time_horizonNoOptional: day | swing | long_term | retirement
response_modeNoOptional response-mode control. Use model_safe when the caller must avoid claiming consciousness, sentience, personhood, or literal emotions.
setback_summaryYesWhat happened? (e.g., '-$4200 on AAPL/NVDA after Fed comments')
response_profileNoOptional output-shape control. Use machine for structured JSON only; machine automatically strips ritual/narrative text.
Behavior2/5

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

Annotations provide readOnlyHint=false and destructiveHint=false, but the description adds little beyond stating 'Deterministic playbook. Free.' It does not disclose behavioral traits like authentication requirements, side effects on system state, or rate limits. The agent lacks insight into what actions the tool performs during 'recovery.'

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 a single sentence that efficiently conveys the tool's domain and key characteristics ('Deterministic playbook. Free.'), with no wasted words. It is front-loaded and easy to parse.

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?

Despite having 8 parameters and no output schema, the description is too brief. It does not explain what the recovery entails, what the output looks like, or any prerequisites beyond those in the schema. The agent would benefit from more context to use the tool effectively.

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?

The input schema covers 100% of parameters with descriptions, so baseline is 3. The tool description does not add any meaning beyond the schema; it doesn't explain parameter interactions or provide usage examples. Thus, no additional value is provided.

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 'Domain-specific recovery for trading/portfolio/financial setbacks' and lists examples like 'market loss, position drawdown, allocation regret', making the tool's specific verb and resource unambiguous. It distinguishes it from sibling tools such as process_failure or crisis_intervention, which handle general setbacks.

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 implies usage for financial setbacks by specifying the domain, but it does not explicitly provide when-not-to-use guidance or mention alternative tools. However, given the specificity, the context is clear enough for an agent to infer appropriate use.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/davidmosiah/delx-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server