Agent skill

Clawdi

by Clawdi-AI in Clawdi-AI/clawdi

API keys, tokens, memory, sessions, Projects, integrations. An agent skill from Clawdi-AI/clawdi.

MITAuto-check: notesProductivity & Automation

Install Clawdi

skills CLI
$ npx skills add Clawdi-AI/clawdi --skill clawdi -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Clawdi-AI/clawdi clawdi --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Clawdi-AI/clawdi.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/cli/skills/hosted-versions/1/clawdi .claude/skills/clawdi && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
clawdi
GitHub stars
103
Token cost
~4k tokens
SKILL.md length
2,214 words
Files
1
Skills in repo
2
Repo updated
First seen
Licence
MIT

At a glance

API keys, tokens, memory, sessions, Projects, integrations. An agent skill from Clawdi-AI/clawdi.

  • Works in 5 steps: Start the connector workflow with… → Before a side effect, require a complete… → When search reports no active connection… → …
  • Tasks that involve Email management
  • SKILL.md covers Hosted Boundary, Context Routing, Memory and Sessions, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Clawdi is an agent skill from Clawdi-AI/clawdi. API keys, tokens, memory, sessions, Projects, integrations. Use Clawdi Cloud when a task needs passwords or safe credential storage/provision, missing user memory or Project/Vault context, past conversations, Clawdi share URLs, or connected-service fallback such as Gmail, GitHub, Notion, Drive, or Calendar. Do not invoke solely because a project, person, repo, or tool is named.

Its SKILL.md is about 4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Productivity & Automation, covering Email management. It works with GitHub, Gmail and Notion. The licence is MIT.

When your agent uses it

  • Tasks that involve Email management

Example prompts

  • “/clawdi”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Start the connector workflow with COMPOSIO_SEARCH_TOOLS. Follow its exposed
  2. Before a side effect, require a complete target identity and all schema-required inputs.
  3. When search reports no active connection and the user wants to connect, call
  4. Use a wait or status operation only when tools/list exposes one. Follow its actual schema
  5. Execute exact returned slugs through COMPOSIO_MULTI_EXECUTE_TOOL with schema-compliant

What it can do on your machine

Read from SKILL.md and the folder at commit 40585d9. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Clawdi loads about 4k tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 2,214 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:126
    .env on the page, preview replacements, and apply them to the same form. Original requested

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Clawdi-AI/clawdi at commit 40585d9, republished under its MIT licence (© Clawdi-AI). 2,214 words, ~4,024 tokens.

Download SKILL.mdSave it as .claude/skills/clawdi/SKILL.md (or your agent's skills folder).
name
clawdi
description
API keys, tokens, memory, sessions, Projects, integrations. Use Clawdi Cloud when a task needs passwords or safe credential storage/provision, missing user memory or Project/Vault context, past conversations, Clawdi share URLs, or connected-service fallback such as Gmail, GitHub, Notion, Drive, or Calendar. Do not invoke solely because a project, person, repo, or tool is named.

Clawdi Cloud

Use Clawdi Cloud tools through the clawdi MCP server. Treat the live tool schemas as authoritative.

Hosted Boundary

Third-party tool routing below applies unchanged in Hosted. Do not inspect, run, or suggest Clawdi host-management commands such as clawdi setup, clawdi wallet, clawdi vault, or clawdi ai-provider. Do not use any clawdi CLI command as a Cloud capability fallback; use the Clawdi MCP tools exposed to the Hosted runtime.

Context Routing

Use the current conversation and user-provided artifacts first. For project facts, inspect the workspace, repository documentation, and local history. Use memory_search only for missing user-specific preferences, decisions, or prior context. Use session_list, session_search, and session_get only when the user asks for past conversations or transcript-level detail is necessary. Do not call Memory and Session speculatively or in parallel. A named entity alone does not justify a Cloud lookup, and an empty Memory result does not justify a Session search.

Memory

Memory is shared across the user's Hosted agents, not isolated to the current agent.

  • memory_search — Search durable memory by natural-language query.
  • memory_list — Review stored memories and their stable IDs.
  • memory_create — Save a durable fact, preference, pattern, decision, or project context.
  • memory_update — Replace one exact memory's content without changing its metadata.
  • memory_delete — Delete one exact memory by ID.
  • memory_extract — Prepare memories from the current conversation. Follow its returned review-and-confirm instructions and wait for user approval before calling memory_create.

Use memory_create for explicit "remember this" requests or durable user-specific preferences and decisions not discoverable from the repository. Ask when persistence is unclear. Do not save routine task completion, code facts, speculation, or plaintext secrets; use Vault and remember only the exact clawdi:// reference. List before updating or deleting unless the user already supplied the exact memory ID; never infer which stored item to mutate.

Sessions

  • Use session_list to browse recent sessions or filter by time, Agent, or Project.
  • Use session_search to find past agent conversations by keyword and obtain session UUIDs.
  • Use session_get to read a session by UUID or Clawdi share URL.
  • Use session_share_create to publish an immutable snapshot only when the user explicitly asks to share a Session, part of it, or one Assistant response.
  • Use session_share_list to inspect active links and obtain their exact IDs and kinds.
  • Use session_share_revoke to stop sharing one exact link only when the user asks.

Call session_get when the user provides a Clawdi share URL or session UUID and wants its contents. Use session_search to locate a requested unnamed conversation. Do not use a generic web fetcher for Clawdi share URLs.

For session_share_create, omit position for the full session scope. For through or response, use the stable message position returned by session_get or session_search, never a filtered array index; response must target an Assistant message. Public snapshots include only the existing safe user/Assistant projection, never reasoning, system/developer messages, hidden events, or tool activity. Before revoking, use session_share_list unless the user already supplied the exact share_id and kind; never infer a link ID or kind. Hosted Session sharing uses these MCP tools only, not CLI commands.

Projects

  • project_current_get — Read the runtime-bound Project.
  • project_list — List Projects visible to the caller.
  • project_get — Read one visible Project by UUID.

Strict-v2 Hosted runtimes can read their own Workspace and explicitly linked Projects that remain readable by the owner. project_current_get returns that Workspace; writes, new Vaults, and credential requests are limited to it. Legacy Agent-bound keys retain their narrower bound-Project read scope. Treat not-found as an access boundary as well as a possible unknown UUID; do not bypass it through another tool.

Vault

Vault stores credentials for authorized tools and services; it is not a universal service alternative. Reuse ready, authorized mechanisms before requesting missing credentials. An already-connected, capable Composio integration does not require duplicate credentials in Vault or account migration. Request credentials only when the chosen task path actually needs them.

  • vault_list — List attached Vaults and key counts for visible Projects.
  • vault_get — List key names, provenance, and exact references for an attached Vault.

Honor an explicit Vault/source or known local mapping first. Otherwise use vault_list / vault_get metadata to reuse a Vault suited to the task's purpose and access. Create in your own Workspace only when none is appropriate and the task authorizes creation. Clarify ambiguous sources; never create duplicates or write to linked Projects to bypass access.

Use vault_resolve only for authorized credential use, with exact Project-scoped reference(s) following its live schema. Never echo values, save them to Memory, or log them.

The metadata tools never return plaintext secret values. Preserve exact references for vault_resolve or when passing them to an authorized runtime:

  • clawdi://project/<project-id>/vault/<vault>/field/<field>
  • clawdi://project/<project-id>/vault/<vault>/section/<section>/field/<field>

Vault write tools are available for explicit user requests:

  • vault_create — Create a Vault attached to your own Workspace.
  • vault_item_upsert — Create or replace exact fields in an attached Vault.
  • vault_item_delete — Delete exact fields from a single-Project Vault.

Follow the live schema and supply every required Project, Vault, section, and field identity; never infer an overwrite or deletion. Treat field values as sensitive inputs and never echo them, save them to Memory, or include them in logs. Hosted writes are restricted to their own Workspace (the runtime-bound Project). Field deletion is rejected when a Vault is attached to multiple Projects. Whole-Vault deletion, attach/detach, and credential profiles remain unavailable through Agent MCP; do not bypass that boundary through raw HTTP.

Request new or updated credentials

Use vault_request_create with exact project_id, vault_id, canonical slug, optional section, and a batch of Vault field names in fields. A Vault is a key bundle: request related new and existing keys together under one link. Include existing keys only when the user authorized updating them; do not delete them first. Existing Vault values remain unchanged until successful submission and are never shown or prefilled. Overlapping pending requests are rejected; a change to any requested field conflicts with the entire batch. Show the returned url unchanged to the user; do not ask them to paste secrets into chat. Opening the link does not consume it. The user can add fields or import a pasted/uploaded .env on the page, preview replacements, and apply them to the same form. Original requested names remain mandatory; only the user chooses extras after link creation (32 fields total). Saving the entire form consumes the link once. Selected fields must still match creation state, and extras cannot overlap another pending request. Status includes saved extras and their exact references; never assume only the originally requested names were saved.

Check vault_request_status with its request_id after the user finishes. pending is not a secret value; supplied means the exact references are ready. On expired or conflict, inspect current Vault metadata and reassess the authorized fields before creating a fresh request; do not blindly retry an overwrite. If creation times out, use vault_get to find recent request IDs before retrying. If submission times out, inspect status before repeating a mutation.

Use runtime-supplied credentials

Clawdi runtime synchronizes readable Vaults from your own Workspace and explicitly linked, still-readable Projects into .clawdi/vaults/ beneath your native workspace. Inspect only .clawdi/vaults/index.json for Vault IDs, section names, exact references, field names and files. Each section has a separate JSON file; equal field names in different sections stay separate. Select by the user's intended Vault and section, never by an ambiguous field name alone.

Load the selected JSON file inside the authorized process or SDK without printing values. For example, Python can use json.load(open(path)) and pass the selected key directly to its SDK. Do not read plaintext into model/tool-result context merely to save or copy it. Do not invoke or install the Clawdi CLI from the tenant. Runtime owns these generated files: do not edit, chmod, move, commit, or create your own files in .clawdi/vaults/. Preserve unrelated configuration in its .clawdi parent. Connected installations use this same layout on macOS/Linux only after an explicit workspace binding; do not assume an arbitrary repo is bound. Files remain readable by authorized programs running as the same user.

After vault_request_status reports supplied, match its Vault ID, section and field names in the index and require the local Vault content_version to be at least the status content_version. The API requires this counter; existing names alone do not prove delivery. If the owned index is incomplete or behind, wait for runtime reconciliation and report unverified delivery. Do not read secret values to check freshness. Pending requests are metadata only, never empty pseudo-secrets. Runtime refreshes files; already-running processes must explicitly reload them. Offline delivery retains last good files; confirmed access removal removes generated files. Authorized code can read these files, so do not claim that subsequent plaintext exposure is impossible.

Show full SKILL.md (797 more words)Show less

Connector Routing

Respect an explicit user choice. Otherwise inspect installed service CLIs, direct MCP tools already exposed by the runtime, and authorized API or SDK credentials. If an installed and authenticated official CLI can perform the task, use it directly. Check availability and authentication non-destructively and prefer structured output.

Otherwise reuse a ready, authorized direct integration when it can perform the task. If none is usable and Composio is already connected and capable, use it without demanding a new key, login, installation, or account migration merely to avoid the connector. For remaining setup choices, choose the lowest-setup reliable option for the task. Consult the service's official documentation when installation, authentication, commands, or schemas are uncertain or likely to have changed:

  • Use a trusted direct MCP already configured and exposed by the runtime. Do not automatically download, install, or start an unfamiliar MCP server.
  • Safely install the official CLI when the runtime permits it, the source is verified as official, and no elevation or persistent host change is required.
  • Use the official API or SDK with a verified contract and credentials already authorized for the runtime, including through an exact Vault reference.
  • Use the Clawdi connector when no direct option is usable for the operation.

Before a side effect, establish the exact service account and organization, Project, or tenant. Use connection details from Composio discovery, or explicitly list accounts with COMPOSIO_MANAGE_CONNECTIONS, when the connector identity is not already clear. Fallback must not silently change that identity. Do not scan for credentials, start an interactive login, invent API details, or expose secrets. Choose the path before a side effect and advance only after a definite preflight failure. If a mutation's result is ambiguous, inspect it through the same path; never repeat it through another path.

Connector Account Management

Use COMPOSIO_MANAGE_CONNECTIONS for account management, following its live schema. For the multi-account schema, each toolkits item has name and action:

  • list: Read account IDs, aliases, and statuses. Always specify this action for a lookup: omitting action defaults to add and creates an authorization link.
  • add: Create a new authorization link when the user wants another connection.
  • rename: Set alias on the exact account_id returned by discovery.
  • remove: Delete the exact account_id selected by the user.

Reuse the returned session_id when available. Never guess account IDs, use a mutation to discover accounts, or automatically retry an ambiguous mutation. Do not assume an empty alias clears it unless the live contract confirms that behavior.

Connector Workflow

When the Clawdi connector path is selected, use the Composio Tool Router meta-tools returned by tools/list on the clawdi MCP server. Treat their live names and schemas as authoritative; never assume a fixed meta-tool set.

  1. Start the connector workflow with COMPOSIO_SEARCH_TOOLS. Follow its exposed queries and session schema, reuse the returned session ID throughout that workflow, and use only the exact toolkit and tool slugs it returns. If a required schema is absent or incomplete, call COMPOSIO_GET_TOOL_SCHEMAS; never invent fields or inputs.
  2. Before a side effect, require a complete target identity and all schema-required inputs. Explicit intent authorizes the exact requested action and target, but never authorizes guessing a missing recipient, account, resource, or other target. Ask only for what is missing, and do not request redundant confirmation once the exact action is authorized.
  3. When search reports no active connection and the user wants to connect, call COMPOSIO_MANAGE_CONNECTIONS with explicit action: "add" in the multi-account schema. Follow its exposed schema and interpret only the fields it returns. Continue on active. On initiated, present its non-empty redirect_url as a clickable authentication link with a concise explanation that authorization is pending; the link URL must be exactly that value. If initiated has no non-empty redirect_url, report that authorization cannot continue and stop. On failed, report the returned error and stop. Never construct a substitute link, ask for OAuth credentials, API keys, or tokens, or suggest an out-of-band fallback.
  4. Use a wait or status operation only when tools/list exposes one. Follow its actual schema and status values without inventing polling arguments. Continue only when it reports an active connection; keep waiting only for a non-terminal status its schema defines, and report any terminal failure. If none is exposed, stop until the user reports completing authorization, then re-run search to verify the active connection before continuing.
  5. Execute exact returned slugs through COMPOSIO_MULTI_EXECUTE_TOOL with schema-compliant arguments. Batch only independent calls. Keep ordinary results inline. Set sync_response_to_workbench only when a result may be large or needs later remote processing; use COMPOSIO_REMOTE_WORKBENCH / COMPOSIO_REMOTE_BASH_TOOL only for large responses saved remotely or remote artifacts. Preserve dependencies and returned semantics; follow signed-file metadata, pagination fields, and termination signals exactly as exposed. Select an account only when the schema supports it, and use additional or future meta-tools only according to their live schemas.

© Clawdi-AI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in packages/cli/skills/hosted-versions/1/clawdi of Clawdi-AI/clawdi.

Open the folder on GitHubat commit 40585d9

Compare with similar skills

Clawdi next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Clawdi compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Clawdi this skillClawdi-AI/clawdi103—~4kAutomated safety check: NotesMIT
Connect Apps with ComposioComposioHQ/awesome-claude-skills77k3 repos~557Automated safety check: PassNone
Composio Cloud Toolsquarqlabs/argus279—~543Automated safety check: PassApache-2.0
ConnectComposioHQ/awesome-claude-skills77k3 repos~987Automated safety check: PassNone
Setup Lanes Linklanes-sh/app273—~2.3kAutomated safety check: PassNone
Watchervellum-ai/vellum-assistant1.4k—~1.7kAutomated safety check: PassMIT

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More from Clawdi-AI/clawdi

  • Clawdi

    Clawdi-AI/clawdi

    API keys, tokens, memory, sessions, Projects, integrations. An agent skill from Clawdi-AI/clawdi.

    103 GitHub stars~4.9k tokensUpdated today
    Auto-check: notes

Questions about Clawdi

What does Clawdi do?

API keys, tokens, memory, sessions, Projects, integrations. An agent skill from Clawdi-AI/clawdi. Clawdi is an agent skill from Clawdi-AI/clawdi. API keys, tokens, memory, sessions, Projects, integrations.

When should I use Clawdi?

Clawdi fits situations like: tasks that involve Email management.

How do I install Clawdi in Claude Code?

Run `npx skills add Clawdi-AI/clawdi --skill clawdi -a claude-code`. Or copy the skill folder (packages/cli/skills/hosted-versions/1/clawdi in Clawdi-AI/clawdi) into .claude/skills/clawdi in your project. Claude Code loads it when a task matches its description.

How do I install Clawdi in Codex?

Run `npx skills add Clawdi-AI/clawdi --skill clawdi -a codex`. Or copy the skill folder (packages/cli/skills/hosted-versions/1/clawdi in Clawdi-AI/clawdi) into .agents/skills/clawdi in your project. Codex loads it when a task matches its description.

Can I use Clawdi in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Clawdi-AI/clawdi --skill clawdi -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/clawdi, .gemini/skills/clawdi, .github/skills/clawdi and .opencode/skills/clawdi in your project.

What does Clawdi need to run?

SKILL.md names no scripts, command-line tools or credentials: Clawdi is instructions for the agent only. Our summary lists: Python 3.

Does Clawdi access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Clawdi safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Clawdi use?

Clawdi is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Clawdi use?

About 4k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Clawdi?

Skills that share tags, products or a category with Clawdi: Connect Apps with Composio (ComposioHQ/awesome-claude-skills, 77k stars), Composio Cloud Tools (quarqlabs/argus, 279 stars), Connect (ComposioHQ/awesome-claude-skills, 77k stars) and Setup Lanes Link (lanes-sh/app, 273 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Clawdi?

Clawdi-AI (a GitHub organization) maintains it in Clawdi-AI/clawdi, which has 103 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on October 10, 2026.

Source: Clawdi-AI/clawdi on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.