Copilot Knowledge Layout

Copilot's behaviour comes from three kinds of knowledge that live in three places. QDash consumes the first two at pinned versions and owns only the third.

Kind	Examples	Home	How QDash gets it
Facts about calibration tasks	Background per task (index.md with a fixed template: intro, Expected plot, Common failures, Parameters to extract; laid out by calibtasks package) and expert-labeled example plots	qdash-task-knowledge, cloned into config/task-knowledge	The repository's generate.py builds task-knowledge.json (figures by path, not embedded); the API serves it to the chat prompt, the evaluation reference, and the qdash_get_task_knowledge tool. The Knowledge page edits it.
Tools and procedures	Tool definitions, "which tool for which question", diagnosis workflows, agent-session workflows	pi-qdash (extensions/, skills/)	Installed into the Agent Runtime image at a pinned version (agent-runtime/Dockerfile)
Product behaviour	Persona, approval cards, ask_user, output language, turn budgets, model catalog	This repository	agent-runtime/src/prompt.ts, config/copilot/*.yaml

The split follows what changes together. A skill that names qdash_list_cooldowns must ship with the version of pi-qdash that defines that tool, so skills live next to the tools. Task physics is the same whether it is read by Ask AI in the analysis sidebar, the chat, or a pi CLI user, so it has one source that every consumer queries. The approval-card flow exists only in the QDash UI, so its instructions stay here.

Rules

• Do not put physics or expected-result descriptions into a skill or into prompt.ts. Add them to the task's index.md in qdash-task-knowledge (intro, Expected plot, Common failures, Parameters to extract) and have the skill say "read the task knowledge for X". A validated plot with its diagnosis goes under examples/ as a demonstration.
• Do not put pi-qdash tool names into prompt.ts. The tool routing guide is the "Preferred tools" section of the pi-qdash qdash skill; the runtime reads it at startup, keeps only the tools it exposes, and inlines it into the system prompt (agent-runtime/src/tool-guide.ts). The rest of that skill and the other skills stay behind read_skill.
• Do not add QDash-only instructions to a pi-qdash skill. pi CLI users get the same skills without the QDash UI.
• The distribution source for agent skills is pi-qdash. .codex/skills/qdash is a development helper for agents that have no pi extension and is not what sessions record.
• Updating knowledge means bumping a version: the pi-qdash version in agent-runtime/Dockerfile, or the task-knowledge checkout under config/task-knowledge. Agent sessions record the skill name, version, and hash they ran with.

Chat prompts

The Pi Agent Runtime is the only chat backend. Its system prompt lives in agent-runtime/src/prompt.ts; the opening message of a chat about a task result is rendered by src/qdash/copilot/prompts/task_chat.py.

Implementation Files

File	Role
agent-runtime/src/prompt.ts	Chat and analysis system prompts
agent-runtime/src/tool-guide.ts	Extracts the tool routing guide from the pi-qdash qdash skill
agent-runtime/src/skill-tool.ts	read_skill, which serves the pi-qdash skills to the model
agent-runtime/src/allowed-tools.ts	Which pi-qdash tools the runtime exposes
src/qdash/datamodel/task_knowledge.py	Loads task-knowledge.json
config/copilot/chat.yaml, config/copilot/evaluation.yaml	Planner models; evaluation model and scoring thresholds