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get_project_context

Return a redacted project snapshot including detected environment, manifest declarations, providers, hooks, and recent audit activity to orient an AI agent in its first call.

Instructions

[agent] Return a single redacted snapshot of everything an AI agent typically wants to know about this project: secrets present (keys + metadata only), detected env, manifest declarations, configured providers, registered hooks, and recent audit activity. Use this as the very first call in a session to orient the agent before it asks for any individual secret; prefer list_secrets for a flat key listing, check_project for manifest-vs-keyring drift, and audit_log for a deeper access trail. Read-only and value-safe — no plaintext secret values are ever included. Returns a single pretty-printed JSON document; shape is intentionally broad and may grow over time, so read defensively.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orgIdNoOrganization identifier for org-scoped secrets. Required only when scope='org'. Example: 'acme-corp'.
scopeNoWhere the secret lives. 'global' = user keyring (default if omitted on reads), 'project' = scoped to projectPath, 'team' = team-shared (needs teamId), 'org' = org-shared (needs orgId).
teamIdNoTeam identifier for team-scoped secrets. Required only when scope='team'. Example: 'acme-platform'.
projectPathNoAbsolute path to the project root for project-scoped secrets and policy resolution. Defaults to the MCP server's current working directory when omitted.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. States 'Read-only and value-safe — no plaintext secret values are ever included.' and warns shape may grow, read defensively. Lacks details on rate limits or errors but covers key safety.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single paragraph with clear front-loading of purpose, then alternatives, safety, and growth note. Every sentence is necessary and adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 4 parameters all documented in schema and no output schema, description explains output contents adequately and warns about evolving shape. Slightly missing specifics on pagination or size limits, but sufficient for typical use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, baseline 3. Description does not add meaning beyond schema for parameters; it focuses on output. No extra parameter context provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool returns a 'redacted snapshot' of project context, listing specific items (secrets, env, manifest, etc.). It distinguishes from siblings by naming alternatives: list_secrets, check_project, audit_log.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says to use this as the very first call to orient the agent, and provides when-not-to-use guidance by preferring listed alternatives for specific needs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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