Project Context

Organization

TenureAI

project-context

Initialize and maintain per-project runtime context (env, secrets, snapshots). Prefer invoking via research-workflow. TRIGGER when: new run needs env setup, preflight before experiment/eval, runtime fields missing (paths, API keys, GPU config, proxy), run snapshot needed, or shared-memory needs project config. DO NOT TRIGGER when: pure research (use deep-research), plan-only (use research-plan), or env already fully resolved.

Overview

Publisher	TenureAI
Repository	`PhD-Zero`
Skill name	`project-context`
Stars	53
Forks	4
Bundled files	3
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
3 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by TenureAI on GitHub. Read the source before you install it.

Installation

Install the Project Context AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/TenureAI/PhD-Zero/tree/main/.agents/skills/project-context
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/TenureAI/PhD-Zero.git /tmp/PhD-Zero
mkdir -p .claude/skills
cp -r /tmp/PhD-Zero/.agents/skills/project-context .claude/skills/project-context

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Project Context in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Project Context on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Project Context is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Project Context

Mission

Provide a reusable, private-by-default context layer for each project so environment information is collected once, reused across runs, and safely isolated from git history.

Scope boundary:

manages runtime context and secrets only
does not store heavy experiment artifacts (checkpoints, dataset caches, large logs)
stores per-project shared-memory source configuration, but not shared-memory records

Trigger

Use this skill when any of these are needed:

first-time project environment bootstrap
preflight checks before experiment/report/eval execution
missing runtime fields during task execution
per-run context snapshot for reproducibility
first use of shared-memory retrieval or export for a project

Private Directory Contract

Store all local runtime state under project root:

<project-root>/.project_local/<project_slug>/context.json
<project-root>/.project_local/<project_slug>/secrets.json
<project-root>/.project_local/<project_slug>/runs/<run_id>/runtime_snapshot.json

Rules:

.project_local/ must be in .gitignore.
context.json is non-sensitive.
secrets.json is sensitive and must never be logged verbatim.
If multiple projects share one orchestration repo, isolate by project_slug.
Initialize .gitignore if missing and append .project_local/ if absent.

Incremental Collection Policy

Do not ask for all fields at once.

infer task type (report|sft|rl|eval|generic)
load existing context.json + secrets.json
auto-detect non-sensitive environment values where possible
if execution target is remote, consume reuse decision from run-governor first; ask only if decision is missing
ask only for missing required fields for the current task
during execution, allow blocker-only delta prompts (e.g. missing API URL/key)
persist immediately for reuse
when shared-memory retrieval/export is needed, ask the user where the local shared-memory repo should live if memory.shared_repo.path is missing

If new missing fields appear later, run preflight again and collect only deltas.

Security Policy

set <project-root>/.project_local and subdirectories to 0700
set secrets.json to 0600
redact sensitive keys in all CLI output (***)
never place secret content in stage reports or commit messages

Run Integration

Recommended order in research execution:

run-governor collects and confirms mode + local|remote target
run-governor initializes run_id
project-context preflight resolves runtime context and consumes remote reuse decision
experiment-execution runs with resolved context
project-context snapshot writes run-scoped frozen context
shared-memory retrieval/export reuses memory.shared_repo.* from context.json

Script

Use helper script:

scripts/project_context.py

Examples:

bash
python3 .agents/skills/project-context/scripts/project_context.py preflight \
  --project-root . \
  --project-slug my-sft-project \
  --task-type sft \
  --run-id 20260303_130000-my-sft-project

bash
python3 .agents/skills/project-context/scripts/project_context.py preflight \
  --project-root . \
  --project-slug my-sft-project \
  --task-type generic \
  --require memory.shared_repo.path

bash
python3 .agents/skills/project-context/scripts/project_context.py show \
  --project-root . \
  --project-slug my-sft-project

bash
python3 .agents/skills/project-context/scripts/project_context.py migrate-layout \
  --project-root . \
  --clean-empty

Required Output for Operations

For each operation, emit:

Project: root and slug
Action: preflight/show/snapshot
State: loaded + newly collected fields
Paths: local/context/secrets/snapshot/runtime/shared-memory paths
Missing: unresolved required fields (if any)

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Project Context AI skill do?

Why use Project Context on TypingMind?

Because you install it once and use it with any model. Project Context is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Project Context in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/TenureAI/PhD-Zero/tree/main/.agents/skills/project-context. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Project Context?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Project Context?

As many as you like. As long as a model supports skills, you can use Project Context with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Project Context AI skill free?

Yes. It is published on GitHub by TenureAI under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Project Context

Mission

Trigger

Private Directory Contract

Incremental Collection Policy

Security Policy

Run Integration

Script

Required Output for Operations

Bundled files

Frequently asked questions

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