MCP Server Builder
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
Summarize critical Watchdog findings for an explicit Speakeasy AI Control Plane project.
$ npx skills add speakeasy-api/gram --skill summarize-critical-watchdog-findings -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install speakeasy-api/gram summarize-critical-watchdog-findings --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/speakeasy-api/gram.git skills-src && mkdir -p .claude/skills && cp -r skills-src/server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings .claude/skills/summarize-critical-watchdog-findings && rm -rf skills-srcUse ~/.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/
Install the "summarize-critical-watchdog-findings" agent skill from https://github.com/speakeasy-api/gram/tree/main/server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings into .claude/skills/summarize-critical-watchdog-findings/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "summarize-critical-watchdog-findings", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/speakeasy-api/gram/tree/main/server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findingsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add speakeasy-api/gram --skill summarize-critical-watchdog-findings -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install speakeasy-api/gram summarize-critical-watchdog-findings --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/speakeasy-api/gram.git skills-src && mkdir -p .agents/skills && cp -r skills-src/server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings .agents/skills/summarize-critical-watchdog-findings && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "summarize-critical-watchdog-findings" agent skill from https://github.com/speakeasy-api/gram/tree/main/server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings into .agents/skills/summarize-critical-watchdog-findings/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "summarize-critical-watchdog-findings", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add speakeasy-api/gram --skill summarize-critical-watchdog-findings -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install speakeasy-api/gram summarize-critical-watchdog-findings --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/speakeasy-api/gram.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings .cursor/skills/summarize-critical-watchdog-findings && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "summarize-critical-watchdog-findings" agent skill from https://github.com/speakeasy-api/gram/tree/main/server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings into .cursor/skills/summarize-critical-watchdog-findings/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "summarize-critical-watchdog-findings", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/speakeasy-api/gram.git --path server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add speakeasy-api/gram --skill summarize-critical-watchdog-findings -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install speakeasy-api/gram summarize-critical-watchdog-findings --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/speakeasy-api/gram.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings .gemini/skills/summarize-critical-watchdog-findings && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "summarize-critical-watchdog-findings" agent skill from https://github.com/speakeasy-api/gram/tree/main/server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings into .gemini/skills/summarize-critical-watchdog-findings/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "summarize-critical-watchdog-findings", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install speakeasy-api/gram summarize-critical-watchdog-findingsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add speakeasy-api/gram --skill summarize-critical-watchdog-findings -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/speakeasy-api/gram.git skills-src && mkdir -p .github/skills && cp -r skills-src/server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings .github/skills/summarize-critical-watchdog-findings && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "summarize-critical-watchdog-findings" agent skill from https://github.com/speakeasy-api/gram/tree/main/server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings into .github/skills/summarize-critical-watchdog-findings/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "summarize-critical-watchdog-findings", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add speakeasy-api/gram --skill summarize-critical-watchdog-findings -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install speakeasy-api/gram summarize-critical-watchdog-findings --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/speakeasy-api/gram.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings .opencode/skills/summarize-critical-watchdog-findings && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "summarize-critical-watchdog-findings" agent skill from https://github.com/speakeasy-api/gram/tree/main/server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings into .opencode/skills/summarize-critical-watchdog-findings/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "summarize-critical-watchdog-findings", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
summarize-critical-watchdog-findingsSummarize critical Watchdog findings for an explicit Speakeasy AI Control Plane project.
Summarize Critical Watchdog Findings is an agent skill from speakeasy-api/gram. Summarize critical Watchdog findings for an explicit Speakeasy AI Control Plane project. Use for a daily security digest or a review of critical findings detected in the last 24 hours, without configuring delivery or scheduling.
Its SKILL.md is about 1.9k 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 Agent Workflows, covering MCP servers. It works with Model Context Protocol. The repository describes itself as: Securely scale AI usage across your organization. A single stack to Connect, Secure, Observe and Distribute agents, MCPs, and Skills within your company. The licence is AGPL-3.0.
6 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit b4c4904. It shows what the files ask for, not the result of running them.
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.
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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Summarize Critical Watchdog Findings loads about 1.9k tokens when it runs. Until then it costs about 66 tokens; SKILL.md has 1,064 words of instructions outside code blocks.
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.
The automated check found no risky patterns in SKILL.md.
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.
The full file from speakeasy-api/gram at commit b4c4904, republished under its AGPL-3.0 licence (© speakeasy-api). 1,064 words, ~1,896 tokens.
.claude/skills/summarize-critical-watchdog-findings/SKILL.md (or your agent's skills folder).Turn an AICP Watchdog review into a concise, channel-neutral digest: establish the authenticated scope, read critical findings, rank the rules that need attention, and report coverage and limitations.
get_platform_context. Verify the expected organization as described above. Stop on a mismatch; do not query another organization as a fallback.list_projects or require complete organization-wide discovery for this path. The findings tool enforces access to the selected project; supplying a selector is not proof of authorization. If both selectors are supplied, ask the user to choose one before querying; in an unattended task with both selectors, return “Digest unavailable” and ask the owner to configure exactly one.list_projects through this same connection and ask the user to choose an exact ID or slug. If discovery is truncated, stop discovery and direct the user to the complete AICP dashboard list; resume only after they supply an exact selector. Do not infer scope from a partial list, guess IDs, or silently select Default. In an unattended task without a selector, return “Digest unavailable” and ask the owner to configure one.
Stop on a missing, ambiguous, or inaccessible project; never substitute another project.to once to the current execution time in UTC and from to exactly 24 hours earlier. Use RFC3339 timestamps. A delayed scheduled run still uses the actual execution time, not its originally scheduled time. Report the resulting rolling window, not “yesterday.”list_watchdog_findings with exactly these choices:severity: "critical". Never broaden severity automatically, including when the result is empty.project_id or project_slug. Pass the selected value unchanged; do not send both selectors.from and to.group_by: ["app"].
Tool names may have connector-specific prefixes. Use the matching registered operations, not the general Event Feed.project_id, or its slug for project_slug. Stop on a mismatch. Validate severity, window, totals, and groups. Require nonnegative total_alerts and total_count, and an explicit truncated flag. Missing fields, mismatched scope, or inconsistent totals are a failed digest, not an empty result. For an untruncated response, the number of groups and sum of their counts must equal total_alerts and total_count. For a truncated response, returned groups/counts must not exceed those totals.Use a short, readable summary (normally under 2,500 characters):
Critical Watchdog digest
Project: <returned project name>
Detection window: <from> inclusive to <to> exclusive, UTC
<total_alerts> rule-level alerts · <total_count> findings
For each displayed rule:
<rule ID>: <count> findings; <users_affected> affected users; <clients_affected> observed apps.Optionally include the top two app buckets for a rule when useful. Preserve observed spellings instead of merging labels. Do not sum affected users or apps across rules: the same user or app can appear in multiple rules.
If both totals are zero after a successful query, replace the rule list with: “No critical Watchdog findings were detected in this project during this reporting window.”
If fewer rules are displayed than total_alerts, state the number not shown. If truncated is true, label the ranking as the top rules among returned results, explicitly state that the tool's rule list is incomplete, and retain the full-window totals. Mark any included truncated app histogram as incomplete too. Never imply an incomplete ranking covers every alert.
End with: “Counts use detection time and include matches from disabled policies. Findings are not proof of blocked activity.”
Only include a dashboard link if it was returned by a trusted tool or explicitly provided by the user. Never construct a URL from guessed routes.
total_alerts counts rule-level groups; total_count counts individual findings. Keep them distinct.first_seen and last_seen are message timestamps and may lie outside the detection window. Do not filter results using them.On tool failure, denied access, scope mismatch, malformed output, or missing configuration, return “Digest unavailable” with a brief, non-sensitive reason and the next step. Do not report zero findings, reuse stale counts, broaden scope, or expose the raw error payload. A failed query says nothing about whether critical findings exist.
A bounded retry for a transient read failure must retain the same verified project and time window. If the tool asks to narrow the window, report that the requested 24-hour digest could not be completed and ask for a separate shorter-window review; do not silently change coverage.
© speakeasy-api, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings of speakeasy-api/gram.
Open the folder on GitHubat commit b4c4904
Summarize Critical Watchdog Findings 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Summarize Critical Watchdog Findings this skillspeakeasy-api/gram | 273 | — | ~1.9k | Automated safety check: Pass | AGPL-3.0 | |
| MCP Server Builderanthropics/skills | 180k | 63 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| MCP Server BuildershareAI-lab/learn-claude-code | 78k | 4 repos | ~1.2k | Automated safety check: Pass | MIT | |
| MCP Integration for Pluginsanthropics/claude-plugins-official | 38k | 11 repos | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| MCP Server Builder with mcp-usemcp-use/mcp-use | 11k | — | ~923 | Automated safety check: Pass | Apache-2.0 | |
| Agents SDKcloudflare/skills | 3k | 2 repos | ~3k | Automated safety check: Pass | Apache-2.0 |
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
shareAI-lab/learn-claude-code
Walks through building MCP servers in Python or TypeScript that expose tools, resources and prompts to Claude, with templates, registration and testing.
anthropics/claude-plugins-official
Explains how to bundle Model Context Protocol servers in a Claude Code plugin, covering config files, stdio, SSE, HTTP and WebSocket server types, and authentication.
mcp-use/mcp-use
Builds, modifies, debugs, migrates and verifies TypeScript MCP servers and MCP Apps with the mcp-use framework, treating the installed package's types as the source of truth.
cloudflare/skills
Build, debug, or review Cloudflare Agents SDK applications using the agents package.
awslabs/cli-agent-orchestrator
Enable, operate, and extend CAO's MCP Apps surface — the host-rendered fleet dashboard visible inside MCP App hosts (Claude Desktop, ChatGPT, VS Code Copilot, Goose, Postman).
speakeasy-api/gram
A skill your agent uses when automating the Speakeasy dashboard in a browser, capturing screenshots, inspecting pages.
speakeasy-api/gram
A skill your agent uses when adding, changing, restyling, reviewing, validating, or previewing a Speakeasy transactional email, in Go or in LMX/MJML — a template<name.go, a TemplateKey constant, a…
speakeasy-api/gram
A skill your agent uses when adding, changing, or styling UI in client/admin (the Speakeasy admin dashboard) that touches shadcn/ui — a button, dialog, table, sidebar, badge, select, tabs, tooltip…
speakeasy-api/gram
A skill your agent uses when adding, editing, reviewing, testing, or locating a reviewed skill distributed with the Platform MCP plugin; triggers include "Platform MCP skill", "platformmcpskills"…
speakeasy-api/gram
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speakeasy-api/gram
A skill your agent uses when gating a feature behind a flag, dogfooding or gradually rolling out a change, choosing between productfeatures and PostHog feature flags, adding or checking a product…
Works with
Categories
Summarize critical Watchdog findings for an explicit Speakeasy AI Control Plane project. Summarize Critical Watchdog Findings is an agent skill from speakeasy-api/gram. Summarize critical Watchdog findings for an explicit Speakeasy AI Control Plane project.
Summarize Critical Watchdog Findings fits situations like: A daily security digest; A review of critical findings detected in the last 24 hours; without configuring delivery.
Run `npx skills add speakeasy-api/gram --skill summarize-critical-watchdog-findings -a claude-code`. Or copy the skill folder (server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings in speakeasy-api/gram) into .claude/skills/summarize-critical-watchdog-findings in your project. Claude Code loads it when a task matches its description.
Run `npx skills add speakeasy-api/gram --skill summarize-critical-watchdog-findings -a codex`. Or copy the skill folder (server/internal/plugins/platform_mcp_skills/summarize-critical-watchdog-findings in speakeasy-api/gram) into .agents/skills/summarize-critical-watchdog-findings in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add speakeasy-api/gram --skill summarize-critical-watchdog-findings -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/summarize-critical-watchdog-findings, .gemini/skills/summarize-critical-watchdog-findings, .github/skills/summarize-critical-watchdog-findings and .opencode/skills/summarize-critical-watchdog-findings in your project.
SKILL.md names no scripts, command-line tools or credentials: Summarize Critical Watchdog Findings is instructions for the agent only.
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.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Summarize Critical Watchdog Findings is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.9k tokens (SKILL.md is roughly 7.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Summarize Critical Watchdog Findings: MCP Server Builder (anthropics/skills, 180k stars), MCP Server Builder (shareAI-lab/learn-claude-code, 78k stars), MCP Integration for Plugins (anthropics/claude-plugins-official, 38k stars) and MCP Server Builder with mcp-use (mcp-use/mcp-use, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
speakeasy-api (a GitHub organization) maintains it in speakeasy-api/gram, which has 273 GitHub stars. The repository holds 40 skills in this directory. The repository was last updated on October 10, 2026.
Source: speakeasy-api/gram on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.