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On GitHub since February 2009

23

Published Tools

5

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39

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Published Tools

4 MCP Servers19 Skillsacross 5 categories

Turns three sandbox environment failures that name neither their cause nor a remedy into a diagnosis with a path forward. Family 1, the Windows workspace ACL: nine reports (#7538, #7622, #7646, #7720, #7750, #7735, #7771, #7804, #7816) of one signature —

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SkillAI Tool
31 dir

Two public tools.restrict() use cases for the dsh harness, applied per agent scope: a per-preset tool ALLOWLIST (#5786: a preset agent inherits the global layer and every ancestor scope layer, so plugin-registered commands leak into a minimal preset) and

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SkillAI Tool
11 dir

Proactive session-log completeness audit for the dsh harness: detects seq gaps, index-reuse, format-version drift, unknown-required types (hard-fail on reload), empty text blocks (#5773), orphan tool calls, and open-turn tails — before replay crashes.

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SkillAI Tool
11 dir

Deployment-level tool-call deadlines for dsh: a tool that never declares ToolDefinition.timeoutMs is dispatched with no deadline at all, so one wedged call (a delegation whose child never settles, a third-party MCP tool that never returns) leaves the turn

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MCP ServerAI Tool
2 dirs

Makes an unattributed model attempt retryable, for the one seam that can tell. Three reports, one missing evidence. Discussion #8321: a `dsh-llm-pi-ai` route that relays an upstream empty response ends the turn, because `classifyPiAiError` has no rule mat

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SkillLLM Tool
1 dir

Cron-driven autonomous task runs for the dsh harness: fire a calendar cron rule and spawn a fresh agent run via ctx.agents.create(), unlike the official @deepseek-ai/dsh-schedule which only messages the live session.

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SkillAI Tool
1 dir

Session-scoped model and effort selection for dsh. Every entry point that names a model for one session also rewrites the deployment default, so a lane cannot launch on a model without re-pointing every later session in the same DSH home: the session mode

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SkillAI Tool
1 dir

Writes the activation report the harness already composes but never files. When a third-party plugin fails to activate — most often because a tool or prompt-section name it registers is already taken — the fiber that threw is unloaded whole, so every tool

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SkillAI Tool
1 dir

Keeps a compaction call from dying on the very route it was meant to shrink away from. When the harness summarizes an oversized history and the summary request is refused by the session's current model - because that model's context window is smaller than

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SkillLLM Tool
1 dir

A tool parameter declared with a type list (["boolean","string"]), an `anyOf` or a `oneOf` is legal JSON Schema, and third-party MCP servers publish them — a code-search server declaring `anyOf [array|string, null]` on its main parameters is the reported

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MCP Servermcp
1 dir

`dsh-mcp-client` registers every tool a connected MCP server lists, unconditionally, so a server advertising 161 tools puts 161 tools and their full JSON schemas into every request that assembles the tool surface (reported as #9385). `ctx.tools.restrict()

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MCP Serveruncategorised
1 dir

MCP tool calls rendered as the calls they are: the dsh Web Tool row is a keyed seat dispatched by wire Tool name, so a family of names that only exists after an MCP server answers tools/list falls back to the generic card — which flattens `mcp__<server>__

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MCP Serveruncategorised
1 dir

A session whose request exceeds the model's context window and whose summarizer cannot fit that same window has no way out: every later message replays the same oversized history into the same 400, so the session is unusable until someone edits the persis

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SkillRAG
1 dir

An empty-identity tool call can be advertised but never answered: tool/call is admitted with callId "", the harness's own assembler only synthesises a fallback id for a missing one (nullish, so an empty string defeats it), and the paired tool/result is th

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SkillLLM Tool
1 dir

Pins a tool call to the identity it was approved with. The registry hands tools/pre-execute listeners the live execution object and documents name/agent/parent/callId/signal/token as readonly, while the object is a plain writable literal with only the arg

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SkillAI Tool
1 dir

Runaway tool-call argument guard for dsh: wrap the llm/stream waterfall and cut a tool call that streams more than a configurable number of arguments bytes, terminating with a routed TOOL_CALL_ARGUMENTS_TOO_LARGE error finish so the oversized call is neve

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SkillLLM Tool
2 dirs

Thinking-loop guard for dsh: observes the llm/stream waterfall and breaks a model that degrades into a loop. Detects three per-call shapes (reasoning-only calls, restated-material calls, self-repeating low-entropy reasoning) and re-fires instead of latchi

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SkillLLM Tool
1 dir

Actionable read_image refusal for dsh: when the harness refuses to read an image because the resolved model route does not declare image input, turn that opaque 'switch to an image-capable model' message into concrete config guidance (declare "input: [tex

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SkillAI Tool
1 dir

Context-overflow classifier guard for dsh: observes the llm/stream waterfall and reclassifies a provider request-size rejection that names an *input* budget (max_prompt_tokens / max_input_tokens) rather than the model's context window. Unrecognized, such

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SkillLLM Tool
1 dir

Steer and new-output preemption for dsh: a new user input (next-step steer) or new output from the awaited job interrupts a blocking job_output(wait: true) read immediately instead of letting it block up to the job-wait cap, so the agent loop reaches its

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SkillAI Tool
1 dir

Thinking-level fallback for dsh: wraps the llm/stream waterfall and re-issues an auxiliary model call the provider rejected for naming an unsupported thinking level (e.g. Google: "Thinking level MINIMAL is not supported for this model"). On that provider

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SkillLLM Tool
1 dir

Cost budget for dsh web_search: bounds the number of billable provider search requests a `web_search` call may initiate (per call / per turn / per session / whole subagent tree) and denies the call with an actionable error once the budget is exhausted. Ex

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SkillAI Tool
1 dir

Per-delegation reasoning effort for dsh subagents: makes AgentOptions.reasoningEffort reach child requests (the agent loop silently ignored it) and adds a subagent_effort tool that accepts reasoning_effort and model per call

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SkillAI Tool
1 dir