https://hoyant-su-agentic-rl.hf.space/gradio_api/mcp/ ↗
Filter agent RL methods by supervision, critic and task setting; retrieve source links and BibTeX.
Agentic RL: Credit Assignment and CLI Agents is a remote MCP server published at hoyant-su-agentic-rl.hf.space. It has been probed 18 times since 9/12/2026. It answered in 18 of them (100.0%), a near-uninterrupted record. Median response time is 493 ms, placing it among the faster endpoints. It offers a narrow, focused set of 8 tools. On the protocol side it still runs 2025-11-25 and has not moved to the newer spec.
Can an LLM agent pick the right tool here — names, descriptions and parameter clarity are assessed.
| Run | Era | Modern | ms | Legacy | ms | Versions |
|---|---|---|---|---|---|---|
| 2026-09-14 02:22:47 | Legacy | 400 | 586 | 200 | 594 | 2025-11-25 |
| 2026-09-14 00:19:26 | Legacy | 400 | 801 | 200 | 797 | 2025-11-25 |
| 2026-09-13 22:17:36 | Legacy | 400 | 564 | 200 | 567 | 2025-11-25 |
| 2026-09-13 21:01:02 | Legacy | 400 | 494 | 200 | 493 | 2025-11-25 |
| 2026-09-13 18:57:30 | Legacy | 400 | 294 | 200 | 353 | 2025-11-25 |
| 2026-09-13 16:52:42 | Legacy | 400 | 341 | 200 | 343 | 2025-11-25 |
| 2026-09-13 14:49:35 | Legacy | 400 | 377 | 200 | 388 | 2025-11-25 |
| 2026-09-13 12:47:19 | Legacy | 400 | 433 | 200 | 438 | 2025-11-25 |
| 2026-09-13 10:45:14 | Legacy | 400 | 807 | 200 | 807 | 2025-11-25 |
| 2026-09-13 08:43:04 | Legacy | 400 | 552 | 200 | 552 | 2025-11-25 |
tools/list structure, inputSchema validity, and a functional smoke test — the components of the 0-100 score.
Tools the server advertised in the latest measurement — measured, not catalog-claimed.
Agentic_RL_list_sourcesList original papers and retrieval coverage. Discover source-linked comparisons of credit assignment, agent memory, selective observation and terminal benchmarks, with JSON, CSV and BibTeX links.
Agentic_RL_search_evidenceSearch original papers on agentic reinforcement learning, credit assignment and CLI agents. Use English keywords (AND), OR and quoted phrases. Return relevant passages, source citations, equations and table cells.
querystringrequiredlimitintegerAgentic_RL_fetch_evidenceFetch a complete original evidence block by the evidence_id returned from search_evidence, including section anchor, version, equations, table cells, links, and attribution.
evidence_idstringrequiredAgentic_RL_dataset_overviewInspect ShellOps and ShellOps-Pro task counts, train/test splits, task types, published schemas, source files, license and citation.
Agentic_RL_search_tasksFind real ShellOps CLI benchmark tasks by case-insensitive literal substring in the complete instruction, task ID or published task type. Empty query lists all tasks. Select partition 'all', 'shellops' or 'shellops_pro'; select published split 'all', 'train_src', 'train' or 'test'. Results are ordered by partition then task ID, with explicit pagination and no relevance scoring. The train subset is not double-counted.
querystringrequiredpartitionstringsplitstringlimitintegeroffsetintegerAgentic_RL_get_taskInspect one published ShellOps or ShellOps-Pro task by its exact task_id and partition ('shellops' or 'shellops_pro'). Returns the complete instruction, actual reward specification, published reference answer/command, file-entry metadata, pinned parquet rows and workspace asset links. File content is available at the source links. No shell execution or solution verification is performed.
task_idstringrequiredpartitionstringrequiredAgentic_RL_list_method_facetsList exact filter values for agent RL credit granularity, supervision, value critics and evaluation settings. Each value reports its source-supported method count.
Agentic_RL_filter_methodsFilter agent RL credit-assignment methods by research conditions and return original section evidence and BibTeX. Discover accepted values with list_method_facets. Filters combine with AND; empty strings leave a facet unrestricted. Unknown critic status never matches no. Results use publication order without a relevance or quality ranking.
credit_granularitystringrequired_supervisionstringlearned_value_criticstringevaluation_settingstringEach block is one measurement round. Green: working response. Amber: responded but the server was returning errors (5xx). Red: no response at all.
Each cell is one probe run. Faded cells are incomplete probes — one leg did not answer, so the era is inconclusive.
The two probe legs separately: modern server/discover and legacy initialize.
Derived by comparing consecutive probes — changes in era, protocol version, build and reachability.
Add this badge to your README — it updates automatically as measurements change.
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Sign up free to seeThe catalog entries whose name and description are closest to this one, found with the same index the search box uses.
Premium agentic endpoint for agentic-credit-line-issuer-mcp.
# Agentic UX MCP **Agentic UX MCP** gives coding agents a machine-readable reference for designing interfaces where AI delegates work and users stay in control. It ships **11 lifecycle patterns** — from intent preview and autonomy dials to progress ledgers and return moments — each with anatomy, do/avoid guidance, limitations, and production examples. Patterns are available as **MCP resources** (`agentic-ux://patterns/{slug}` and `agentic-ux://library/full`) so agents can attach specs directly to context. For reviews, **`review_agent_flow`** returns a structured audit kit: lifecycle rubric, empty report schema, and prioritized pattern recommendations for a specific agent flow. **Prompts** provide guided entry points for audits and spec-first implementation. **Best for:** designers and builders shipping long-running agents in Cursor, Replit, research tools, and support automation — anywhere users delegate work and need visibility, consent, and recovery. **No configuration required.
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