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CompletionKit

com.completionkit/evals
IA et agents Outils développeur Public et accessible MCP 2026-07-28

Ce que fait ce MCP

Runs prompt evaluation workflows over datasets using deterministic checks and LLM judges, with metrics, scoring runs, agreements, and versioned prompts.

Capacités

Outils

54 outils
agreements_create
Upsert an agreement for (run, response, metric, created_by). Verdict is one of agree, disagree, borderline. corrected_score (1..5) is required when verdict is 'disagree'.
Schéma d’entrée 
{'type': 'object', 'required': ['run_id', 'response_id', 'metric_id', 'verdict'], 'properties': {'note': {'type': 'string'}, 'run_id': {'type': 'integer'}, 'verdict': {'enum': ['agree', 'disagree', 'borderline'], 'type': 'string'}, 'metric_id': {'type': 'integer'}, 'created_by': {'type': 'string'}, 'response_id': {'type': 'integer'}, 'corrected_score': {'type': 'number'}}}
agreements_list
List agreements. Filter by run_id, response_id, metric_id, or created_by.
Schéma d’entrée 
{'type': 'object', 'required': [], 'properties': {'run_id': {'type': 'integer'}, 'metric_id': {'type': 'integer'}, 'created_by': {'type': 'string'}, 'response_id': {'type': 'integer'}}}
datasets_create
Create a dataset with CSV data. First row is the header. Two column names are recognized specially: "expected_output" is each row's answer key (ground truth) given to the judge and to checks that compare against the row's expected value, and "actual_output" is a pre-made output to score in a prompt-less run. Both are overridable per run (expected_column / output_column). Every column is also available to the prompt as a variable.
Schéma d’entrée 
{'type': 'object', 'required': ['name', 'csv_data'], 'properties': {'name': {'type': 'string'}, 'csv_data': {'type': 'string'}, 'tag_names': {'type': 'array', 'items': {'type': 'string'}}}}
datasets_create_from_url
Create a dataset by downloading CSV from a URL instead of inlining it. Use this for large datasets: pass a public http(s) URL and the server fetches the CSV directly, so the data never has to pass through the tool-call arguments. The URL is SSRF-checked and the download is capped at 10MB. First row is the header; the "expected_output" (answer key) and "actual_output" (pre-made output) columns are recognized specially, overridable per run.
Schéma d’entrée 
{'type': 'object', 'required': ['name', 'url'], 'properties': {'url': {'type': 'string', 'description': 'Public http(s) URL of the CSV file to download.'}, 'name': {'type': 'string'}, 'tag_names': {'type': 'array', 'items': {'type': 'string'}}}}
datasets_delete
Delete a dataset
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
datasets_get
Get a dataset by ID
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
datasets_list
List all datasets
Schéma d’entrée 
{'type': 'object', 'required': [], 'properties': {}}
datasets_update
Update a dataset
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}, 'name': {'type': 'string'}, 'csv_data': {'type': 'string'}, 'tag_names': {'type': 'array', 'items': {'type': 'string'}}}}
judges_compare
Compare two versions of one metric's agreement stats side by side. Requires metric_id, metric_version_a_id, and metric_version_b_id (both versions must belong to that metric). Unavailable for check metrics.
Schéma d’entrée 
{'type': 'object', 'required': ['metric_id', 'metric_version_a_id', 'metric_version_b_id'], 'properties': {'metric_id': {'type': 'integer'}, 'metric_version_a_id': {'type': 'integer'}, 'metric_version_b_id': {'type': 'integer'}}}
judges_replay
Create a scoring run for the current judge over a dataset's existing outputs (wraps runs_create with prompt_id omitted and output_column supplied). This only sets up the run; call runs_generate to actually re-judge the outputs so you can compare against human verdicts.
Schéma d’entrée 
{'type': 'object', 'required': ['name', 'metric_id', 'dataset_id', 'judge_model'], 'properties': {'name': {'type': 'string'}, 'metric_id': {'type': 'integer'}, 'dataset_id': {'type': 'integer'}, 'judge_model': {'type': 'string'}, 'output_column': {'type': 'string', 'description': 'Dataset column with the existing outputs to grade. Defaults to actual_output.'}}}
metric_groups_create
Create a metric group
Schéma d’entrée 
{'type': 'object', 'required': ['name'], 'properties': {'name': {'type': 'string'}, 'tag_names': {'type': 'array', 'items': {'type': 'string'}}, 'metric_ids': {'type': 'array', 'items': {'type': 'integer'}}, 'description': {'type': 'string'}}}
metric_groups_delete
Delete a metric group
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
metric_groups_get
Get a metric group by ID
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
metric_groups_list
List all metric groups
Schéma d’entrée 
{'type': 'object', 'required': [], 'properties': {}}
metric_groups_update
Update a metric group
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}, 'name': {'type': 'string'}, 'tag_names': {'type': 'array', 'items': {'type': 'string'}}, 'metric_ids': {'type': 'array', 'items': {'type': 'integer'}}, 'description': {'type': 'string'}}}
metrics_create
Create a metric with evaluation criteria. For a deterministic check set metric_type:"check" and check_config. Per-kind required keys: value (contains/not_contains/equals), pattern (regex), json_path+expected (json_path_equals), min and/or max (length_bounds); valid_json takes no extra keys. target_path is required when target is json_path. For contains, not_contains, and equals, set compare_to:"expected" to grade against each row's own expected_output (ground truth) instead of a constant value (drop value); add expected_path to dig into the expected value when it is JSON.
Schéma d’entrée 
{'type': 'object', 'required': ['name'], 'properties': {'name': {'type': 'string'}, 'tag_names': {'type': 'array', 'items': {'type': 'string'}}, 'instruction': {'type': 'string'}, 'metric_type': {'enum': ['llm_judge', 'check'], 'type': 'string'}, 'check_config': {'type': 'object', 'properties': {'max': {'type': 'integer'}, 'min': {'type': 'integer'}, 'trim': {'type': 'boolean'}, 'value': {'type': 'string'}, 'target': {'enum': ['response_text', 'input_data', 'json_path'], 'type': 'string'}, 'pattern': {'type': 'string'}, 'expected': {}, 'json_path': {'type': 'string'}, 'multiline': {'type': 'boolean'}, 'check_kind': {'enum': ['contains', 'not_contains', 'equals', 'regex', 'valid_json', 'json_path_equals', 'length_bounds'], 'type': 'string'}, 'compare_to': {'enum': ['constant', 'expected'], 'type': 'string'}, 'target_path': {'type': 'string'}, 'expected_path': {'type': 'string'}, 'case_sensitive': {'type': 'boolean'}}}, 'rubric_bands': {'type': 'array', 'items': {'type': 'object', 'properties': {'stars': {'type': 'integer'}, 'description': {'type': 'string'}}}}}}
metrics_delete
Delete a metric
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
metrics_get
Get a metric by ID
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
metrics_list
List all metrics
Schéma d’entrée 
{'type': 'object', 'required': [], 'properties': {}}
metrics_suggest_variants
Ask the model to rewrite the metric's judge instruction in N variants targeted at the recent disagreements. Each variant is saved as a draft MetricVersion with source="suggestion". Returns the persisted drafts. Stripe-metering hooks fire via ActiveSupport::Notifications under completion_kit.judge_suggestion.generated.
Schéma d’entrée 
{'type': 'object', 'required': ['metric_id'], 'properties': {'count': {'type': 'integer', 'description': 'How many variants to request (default 1, max 3). One focused rewrite beats five reworded copies.'}, 'model': {'type': 'string', 'description': 'Override the model used to generate variants. Defaults to the configured judge model or an available judging model.'}, 'metric_id': {'type': 'integer'}}}
metrics_update
Update a metric. For a deterministic check set metric_type:"check" and check_config. Per-kind required keys: value (contains/not_contains/equals), pattern (regex), json_path+expected (json_path_equals), min and/or max (length_bounds); valid_json takes no extra keys. target_path is required when target is json_path. For contains, not_contains, and equals, set compare_to:"expected" to grade against each row's own expected_output (ground truth) instead of a constant value (drop value); add expected_path to dig into the expected value when it is JSON.
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}, 'name': {'type': 'string'}, 'tag_names': {'type': 'array', 'items': {'type': 'string'}}, 'instruction': {'type': 'string'}, 'metric_type': {'enum': ['llm_judge', 'check'], 'type': 'string'}, 'check_config': {'type': 'object', 'properties': {'max': {'type': 'integer'}, 'min': {'type': 'integer'}, 'trim': {'type': 'boolean'}, 'value': {'type': 'string'}, 'target': {'enum': ['response_text', 'input_data', 'json_path'], 'type': 'string'}, 'pattern': {'type': 'string'}, 'expected': {}, 'json_path': {'type': 'string'}, 'multiline': {'type': 'boolean'}, 'check_kind': {'enum': ['contains', 'not_contains', 'equals', 'regex', 'valid_json', 'json_path_equals', 'length_bounds'], 'type': 'string'}, 'compare_to': {'enum': ['constant', 'expected'], 'type': 'string'}, 'target_path': {'type': 'string'}, 'expected_path': {'type': 'string'}, 'case_sensitive': {'type': 'boolean'}}}, 'rubric_bands': {'type': 'array', 'items': {'type': 'object', 'properties': {'stars': {'type': 'integer'}, 'description': {'type': 'string'}}}}}}
metric_versions_dismiss
Destroy a draft MetricVersion (use for either source: 'edit' or source: 'suggestion'). Published versions are refused — to demote a published version, publish a different one as current instead.
Schéma d’entrée 
{'type': 'object', 'required': ['metric_version_id'], 'properties': {'metric_version_id': {'type': 'integer'}}}
metric_versions_list
List every MetricVersion (drafts + published) for a metric, newest first. Each row carries version_number, state, source, current flag, and timestamps.
Schéma d’entrée 
{'type': 'object', 'required': ['metric_id'], 'properties': {'metric_id': {'type': 'integer'}}}
metric_versions_publish
Publish a MetricVersion as the live version of its metric. Works for both 'draft → published' and 'revert to an older published version → current'. Transactionally flips current, demotes peers, and writes the version's instruction + rubric_bands back onto the metric so the judge grades against it.
Schéma d’entrée 
{'type': 'object', 'required': ['metric_version_id'], 'properties': {'metric_version_id': {'type': 'integer'}}}
promptfoo_import
Import a promptfooconfig.yaml. Creates a prompt, a dataset from the test vars, and metrics from the assert blocks (llm-rubric/g-eval become judge metrics; contains/equals/regex/is-json become deterministic check metrics). Returns a summary of what mapped and what was skipped and why; nothing is dropped silently.
Schéma d’entrée 
{'type': 'object', 'required': ['config'], 'properties': {'config': {'type': 'string', 'description': 'The full promptfooconfig.yaml contents.'}}}
prompts_create
Create a prompt
Schéma d’entrée 
{'type': 'object', 'required': ['name', 'template', 'llm_model'], 'properties': {'name': {'type': 'string'}, 'template': {'type': 'string'}, 'llm_model': {'type': 'string'}, 'tag_names': {'type': 'array', 'items': {'type': 'string'}}, 'description': {'type': 'string'}}}
prompts_delete
Delete a prompt
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
prompts_get
Get a prompt by ID
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer', 'description': 'Prompt ID'}}}
prompts_list
List all prompts
Schéma d’entrée 
{'type': 'object', 'required': [], 'properties': {}}
prompts_publish
Publish a prompt version, making it the current version
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
prompts_suggest_improvement
Suggest an improved version of a prompt, grounded in a run's test results and judge feedback. Analyzes the run's responses, scores, and reviews, then returns reasoning plus a rewritten template (preserving {{variables}}) and persists it as a Suggestion. Requires a run that has a prompt (not a scoring-only run).
Schéma d’entrée 
{'type': 'object', 'required': ['run_id'], 'properties': {'run_id': {'type': 'integer', 'description': 'The run whose results ground the improvement.'}}}
prompts_update
Update a prompt. If the prompt already has runs, this creates a new DRAFT version (current=false) rather than editing in place or publishing — promote it with prompts_publish — so an agent's edits don't go live without a gate. If it has no runs, it is updated in place.
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}, 'name': {'type': 'string'}, 'template': {'type': 'string'}, 'llm_model': {'type': 'string'}, 'tag_names': {'type': 'array', 'items': {'type': 'string'}}, 'description': {'type': 'string'}}}
provider_credentials_create
Create a provider credential
Schéma d’entrée 
{'type': 'object', 'required': ['provider', 'api_key'], 'properties': {'api_key': {'type': 'string'}, 'provider': {'enum': ['openai', 'anthropic', 'ollama', 'openrouter', 'azure_foundry'], 'type': 'string'}, 'api_version': {'type': 'string'}, 'api_endpoint': {'type': 'string'}}}
provider_credentials_delete
Delete a provider credential
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
provider_credentials_get
Get a provider credential by ID (API key is not exposed)
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
provider_credentials_list
List all provider credentials (API keys are not exposed)
Schéma d’entrée 
{'type': 'object', 'required': [], 'properties': {}}
provider_credentials_update
Update a provider credential
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}, 'api_key': {'type': 'string'}, 'provider': {'type': 'string'}, 'api_version': {'type': 'string'}, 'api_endpoint': {'type': 'string'}}}
responses_get
Get a specific response
Schéma d’entrée 
{'type': 'object', 'required': ['run_id', 'id'], 'properties': {'id': {'type': 'integer'}, 'run_id': {'type': 'integer'}}}
responses_list
List responses for a run, in row order. Returns {total, limit, offset, returned, responses}. Defaults to 50 rows because full payloads are large: use "fields" to drop the bodies, "min_score"/"max_score" to isolate low scorers, and sort "score_asc" to read the worst rows first. For per-metric averages of the whole run use runs_get instead of aggregating here.
Schéma d’entrée 
{'type': 'object', 'required': ['run_id'], 'properties': {'sort': {'enum': ['id', 'score_asc', 'score_desc'], 'type': 'string', 'description': 'Row order; defaults to "id".'}, 'limit': {'type': 'integer', 'description': 'Rows to return; defaults to 50, capped at 500.'}, 'fields': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Only return these keys, keeping the payload small. Response keys: id, run_id, input_data, response_text, expected_output, created_at, score, reviewed, reviews, status, attempts, row_index, error. Prefix with "reviews." to trim each review, e.g. ["score", "reviews.metric_name", "reviews.ai_score"]. id is always included.'}, 'offset': {'type': 'integer', 'description': 'Rows to skip before returning results.'}, 'run_id': {'type': 'integer'}, 'status': {'type': 'string', 'description': 'Filter by row status: pending, retrying, succeeded or failed.'}, 'max_score': {'type': 'number', 'description': 'Only rows whose average judge score is at most this. Use with sort "score_asc" for failure-mode analysis.'}, 'min_score': {'type': 'number', 'description': 'Only rows whose average judge score is at least this.'}}}
runs_create
Create a run. Omit prompt_id and provide output_column to score existing outputs by grading a pre-existing dataset column instead of generating new ones.
Schéma d’entrée 
{'type': 'object', 'required': ['name'], 'properties': {'name': {'type': 'string'}, 'prompt_id': {'type': 'integer'}, 'tag_names': {'type': 'array', 'items': {'type': 'string'}}, 'dataset_id': {'type': 'integer'}, 'max_tokens': {'type': 'integer', 'description': "Cap on generated tokens per row. Leave unset to use the provider client's default, which is what silently truncates long outputs and makes the judge score malformed JSON. Set it to whatever the prompt uses in production so the eval matches."}, 'metric_ids': {'type': 'array', 'items': {'type': 'integer'}}, 'judge_model': {'type': 'string'}, 'temperature': {'type': 'number', 'description': 'Sampling temperature for generation, 0 to 1. Leave it unset, which is the default, and no temperature is sent at all, so the model applies its own. Most current frontier models refuse the parameter outright; set it only when you are targeting a model that honours it, such as anything served locally through Ollama. A refused value is re-sent without one and the run is flagged temperature_ignored.'}, 'output_column': {'type': 'string', 'description': 'Dataset column to grade when prompt_id is omitted; defaults to "actual_output".'}, 'expected_column': {'type': 'string', 'description': 'Dataset column holding each row\'s answer key / ground truth, graded by checks with compare_to "expected" and passed to the judge; defaults to "expected_output".'}, 'metric_group_id': {'type': 'integer', 'description': 'Attach the metrics belonging to this metric group (its current metric_ids). Ignored when metric_ids is also given.'}, 'judge_temperature': {'type': 'number', 'description': "Sampling temperature for the judge, 0 to 1. Defaults to 0 so re-judging the same output gives the same score. Raise it only to measure judge variance on purpose; any value above 0 makes the run's scores irreproducible."}}}
runs_delete
Delete a run
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
runs_generate
Start a run. Required for every run, including score-only runs (no prompt): generates responses with the prompt when there is one, otherwise copies the graded dataset column and grades it.
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
runs_get
Get a run by ID, including "metric_averages": a per-metric breakdown with each metric's average score (or pass rate for checks), how many rows it graded, and how many scored low. Use this to find the metric dragging a prompt down without listing responses.
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
runs_list
List all runs
Schéma d’entrée 
{'type': 'object', 'required': [], 'properties': {}}
runs_regrade
Re-grade a run's existing responses with its currently attached metrics, without regenerating. Use after attaching or editing metrics on an already-generated run.
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
runs_rerun
Create and start a fresh copy of a run with the same prompt, dataset, metrics, and settings. Use when the judge changed and you want a clean run instead of mixing versions.
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
runs_retry_failures
Re-run only the failed responses of a run, optionally limited to specific response ids via "only".
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}, 'only': {'type': 'array', 'items': {'type': 'integer'}}}}
runs_update
Update a run
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}, 'name': {'type': 'string'}, 'tag_names': {'type': 'array', 'items': {'type': 'string'}}, 'dataset_id': {'type': 'integer'}, 'max_tokens': {'type': 'integer', 'description': "Cap on generated tokens per row. Leave unset to use the provider client's default, which is what silently truncates long outputs and makes the judge score malformed JSON. Set it to whatever the prompt uses in production so the eval matches."}, 'metric_ids': {'type': 'array', 'items': {'type': 'integer'}}, 'judge_model': {'type': 'string'}, 'temperature': {'type': 'number', 'description': 'Sampling temperature for generation, 0 to 1. Leave it unset, which is the default, and no temperature is sent at all, so the model applies its own. Most current frontier models refuse the parameter outright; set it only when you are targeting a model that honours it, such as anything served locally through Ollama. A refused value is re-sent without one and the run is flagged temperature_ignored.'}, 'output_column': {'type': 'string'}, 'expected_column': {'type': 'string'}, 'metric_group_id': {'type': 'integer', 'description': "Replace the run's metrics with those belonging to this metric group. Ignored when metric_ids is also given."}, 'judge_temperature': {'type': 'number', 'description': "Sampling temperature for the judge, 0 to 1. Defaults to 0 so re-judging the same output gives the same score. Raise it only to measure judge variance on purpose; any value above 0 makes the run's scores irreproducible."}}}
tags_create
Create a tag. Color is auto-assigned.
Schéma d’entrée 
{'type': 'object', 'required': ['name'], 'properties': {'name': {'type': 'string'}}}
tags_delete
Delete a tag. Removes the tag from every linked metric, prompt, run, and dataset.
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
tags_get
Get a tag by ID
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}}}
tags_list
List all tags
Schéma d’entrée 
{'type': 'object', 'required': [], 'properties': {}}
tags_update
Rename a tag.
Schéma d’entrée 
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'integer'}, 'name': {'type': 'string'}}}
usage_get
Get this organization's plan usage and limits for the current billing period: runs and prompt fetches used, their limits, how many remain, and when the period resets. Call this to pre-check quota before starting runs. Runs are hard-blocked once the run limit is reached (with a small grace band), so a run over the limit will fail with run_limit_reached.
Schéma d’entrée 
{'type': 'object', 'required': [], 'properties': {}}
Historique

Modifications récentes des outils

Ajouté
usage_get
17 September 2026 12:34
Ajouté
promptfoo_import
17 September 2026 12:34
Ajouté
judges_compare
17 September 2026 12:34
Ajouté
judges_replay
17 September 2026 12:34
Ajouté
agreements_create
17 September 2026 12:34
Ajouté
agreements_list
17 September 2026 12:34
Ajouté
tags_delete
17 September 2026 12:34
Ajouté
tags_update
17 September 2026 12:34
Ajouté
tags_create
17 September 2026 12:34
Ajouté
tags_get
17 September 2026 12:34
Ajouté
tags_list
17 September 2026 12:34
Ajouté
provider_credentials_delete
17 September 2026 12:34
Ajouté
provider_credentials_update
17 September 2026 12:34
Ajouté
provider_credentials_create
17 September 2026 12:34
Ajouté
provider_credentials_get
17 September 2026 12:34
Ajouté
provider_credentials_list
17 September 2026 12:34
Ajouté
metric_versions_dismiss
17 September 2026 12:34
Ajouté
metric_versions_publish
17 September 2026 12:34
Ajouté
metric_versions_list
17 September 2026 12:34
Ajouté
metric_groups_delete
17 September 2026 12:34
Ajouté
metric_groups_update
17 September 2026 12:34
Ajouté
metric_groups_create
17 September 2026 12:34
Ajouté
metric_groups_get
17 September 2026 12:34
Ajouté
metric_groups_list
17 September 2026 12:34
Ajouté
metrics_suggest_variants
17 September 2026 12:34
Ajouté
metrics_delete
17 September 2026 12:34
Ajouté
metrics_update
17 September 2026 12:34
Ajouté
metrics_create
17 September 2026 12:34
Ajouté
metrics_get
17 September 2026 12:34
Ajouté
metrics_list
17 September 2026 12:34
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