Causal Decision Agent

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discos_plot

Read-only

Visualize distributional synthetic control outputs: quantile treatment effects, counterfactual comparisons, gaps over time, and donor weights.

Instructions

Visualise distributional synthetic control results.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`ax`	No	Pre-existing axes for the plot.
`type`	No	default 'quantile_effect' ``'quantile_effect'``: treatment effect Delta(tau) across quantiles with CIs. ``'quantile_comparison'``: overlay treated vs. counterfactual quantile functions. ``'gap'``: gap plot (treated - synthetic) over time. ``'weights'``: horizontal bar chart of donor weights.	quantile_effect
`color`	No	Primary plot colour.	#2C3E50
`title`	No	Plot title override.
`detail`	No	Payload depth: 'minimal' (~150 tokens) for sub-step calls where only the point estimate is needed; 'standard' (~1K tokens) for diagnostics + coefficient table; 'agent' (~2K tokens, default) adds violations / next_steps / suggested_functions so the LLM can plan its next call without another round-trip.	agent
`result`	Yes	Output from ``discos()`` or ``qqsynth()``.
`figsize`	No	Figure size.
`ci_alpha`	No	Transparency for CI band.
`as_handle`	No	If true, cache the fitted result on the server and return result_id + result_uri alongside the JSON payload so a subsequent tools/call can chain without re-running.
`data_path`	No	Absolute path or URL to a data file. Supported: .csv / .tsv / .txt (delimited), .parquet / .pq, .feather / .arrow, .xlsx / .xls, .dta (Stata), .json / .jsonl. Schemes: file://, s3://, gs://, https://.
`result_id`	No	Optional handle to a previously-fitted result (returned by an earlier call when as_handle=true). Tools that operate on a fitted object accept this in place of re-supplying data_path + columns.
`data_columns`	No	Optional column projection. Parquet/Feather/Stata loaders honour this for fast partial reads.
`data_sample_n`	No	Optional uniform random subsample size (seed=0, deterministic) — useful on huge panels.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 15, 2026

TDQS

C2.9/5.0

Behavior2/5

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

With readOnlyHint=true already declared, the description adds no additional behavioral context. It does not mention plot types, caching via as_handle, or data loading via data_path. It is consistent with the annotation but adds no value beyond it.

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 a single short sentence, which is concise and front-loaded. However, it is so minimal that it may under-specify the tool's scope, though the name and schema compensate.

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 a rich schema and output schema, the description gives no context on prerequisites (e.g., needing a fitted result from discos()/qqsynth()), no guidance on plot type selection, and no mention of the wide range of parameters. An agent would need to rely entirely on the schema and name, making the description inadequate for a tool of this complexity.

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 all parameters are documented. The description itself adds no parameter-specific meaning, but the baseline of 3 is appropriate because the schema handles the semantics.

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 states a clear action ('Visualise') and a specific resource ('distributional synthetic control results'), which aligns with the tool's name. However, it does not explicitly mention the source functions (discos/qqsynth) or distinguish from generic plotting tools like plot_from_result, though the name largely conveys that.

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?

The description provides no guidance on when to use this tool versus alternatives such as plot_from_result, synthplot, or qqsynth. It does not mention that this requires a result from discos() or qqsynth(), nor any exclusions or fallback tools.

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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