OpenHarness End-to-End Evals
HKUDS/OpenHarness
Validates OpenHarness features by running real multi-turn agent loops with live LLM calls against an unfamiliar codebase, checking actual tool execution.
Implement a new Packmind AI agent rendering/deployer pipeline (single-file or multi-file) with type and registry wiring, frontend UI/docs updates, and thorough unit/integration tests to reliably…
$ npx skills add PackmindHub/packmind --skill adding-ai-agent-rendering-system -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install PackmindHub/packmind adding-ai-agent-rendering-system --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/PackmindHub/packmind.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/.agents/skills/adding-ai-agent-rendering-system .claude/skills/adding-ai-agent-rendering-system && 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 "adding-ai-agent-rendering-system" agent skill from https://github.com/PackmindHub/packmind/tree/main/packages/.agents/skills/adding-ai-agent-rendering-system into .claude/skills/adding-ai-agent-rendering-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adding-ai-agent-rendering-system", 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/PackmindHub/packmind/tree/main/packages/.agents/skills/adding-ai-agent-rendering-systemType 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 PackmindHub/packmind --skill adding-ai-agent-rendering-system -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install PackmindHub/packmind adding-ai-agent-rendering-system --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/PackmindHub/packmind.git skills-src && mkdir -p .agents/skills && cp -r skills-src/packages/.agents/skills/adding-ai-agent-rendering-system .agents/skills/adding-ai-agent-rendering-system && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "adding-ai-agent-rendering-system" agent skill from https://github.com/PackmindHub/packmind/tree/main/packages/.agents/skills/adding-ai-agent-rendering-system into .agents/skills/adding-ai-agent-rendering-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adding-ai-agent-rendering-system", 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 PackmindHub/packmind --skill adding-ai-agent-rendering-system -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install PackmindHub/packmind adding-ai-agent-rendering-system --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/PackmindHub/packmind.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/packages/.agents/skills/adding-ai-agent-rendering-system .cursor/skills/adding-ai-agent-rendering-system && 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 "adding-ai-agent-rendering-system" agent skill from https://github.com/PackmindHub/packmind/tree/main/packages/.agents/skills/adding-ai-agent-rendering-system into .cursor/skills/adding-ai-agent-rendering-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adding-ai-agent-rendering-system", 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/PackmindHub/packmind.git --path packages/.agents/skills/adding-ai-agent-rendering-system--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 PackmindHub/packmind --skill adding-ai-agent-rendering-system -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install PackmindHub/packmind adding-ai-agent-rendering-system --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/PackmindHub/packmind.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/packages/.agents/skills/adding-ai-agent-rendering-system .gemini/skills/adding-ai-agent-rendering-system && 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 "adding-ai-agent-rendering-system" agent skill from https://github.com/PackmindHub/packmind/tree/main/packages/.agents/skills/adding-ai-agent-rendering-system into .gemini/skills/adding-ai-agent-rendering-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adding-ai-agent-rendering-system", 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 PackmindHub/packmind adding-ai-agent-rendering-systemInstalls 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 PackmindHub/packmind --skill adding-ai-agent-rendering-system -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/PackmindHub/packmind.git skills-src && mkdir -p .github/skills && cp -r skills-src/packages/.agents/skills/adding-ai-agent-rendering-system .github/skills/adding-ai-agent-rendering-system && 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 "adding-ai-agent-rendering-system" agent skill from https://github.com/PackmindHub/packmind/tree/main/packages/.agents/skills/adding-ai-agent-rendering-system into .github/skills/adding-ai-agent-rendering-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adding-ai-agent-rendering-system", 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 PackmindHub/packmind --skill adding-ai-agent-rendering-system -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install PackmindHub/packmind adding-ai-agent-rendering-system --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/PackmindHub/packmind.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/packages/.agents/skills/adding-ai-agent-rendering-system .opencode/skills/adding-ai-agent-rendering-system && 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 "adding-ai-agent-rendering-system" agent skill from https://github.com/PackmindHub/packmind/tree/main/packages/.agents/skills/adding-ai-agent-rendering-system into .opencode/skills/adding-ai-agent-rendering-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adding-ai-agent-rendering-system", 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.
adding-ai-agent-rendering-systemImplement a new Packmind AI agent rendering/deployer pipeline (single-file or multi-file) with type and registry wiring, frontend UI/docs updates, and thorough unit/integration tests to reliably…
Adding AI Agent Rendering System is an agent skill from PackmindHub/packmind. Implement a new Packmind AI agent rendering/deployer pipeline (single-file or multi-file) with type and registry wiring, frontend UI/docs updates, and thorough unit/integration tests to reliably support additional coding assistants and distribution formats when introducing a new agent integration or render mode.
Its SKILL.md is about 4.5k 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 Testing & QA, covering Frontend development and Integration testing. The repository describes itself as: Packmind seamlessly captures your engineering playbook and turns it into AI context, guardrails, and governance. The licence is Apache-2.0.
12 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 8a10541. 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 (its code samples are typescript and markdown).
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.
Adding AI Agent Rendering System loads about 4.5k tokens when it runs. Until then it costs about 87 tokens; SKILL.md has 1,450 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 PackmindHub/packmind at commit 8a10541, republished under its Apache-2.0 licence (© PackmindHub). 1,450 words, ~4,543 tokens.
.claude/skills/adding-ai-agent-rendering-system/SKILL.md (or your agent's skills folder).Add a new AI agent rendering system to Packmind, supporting both single-file (like AGENTS.md) and multi-file (like Cursor/Continue) patterns, including type definitions, deployer implementation, registry registration, frontend UI integration, documentation updates, and comprehensive tests following Packmind test standards.
When adding support for a new AI coding assistant (e.g., Continue, Cursor, Claude Code, GitHub Copilot, OpenCode)
When implementing a new rendering format for standards and recipes distribution
When extending Packmind to support additional AI agent integrations
When creating a new deployer that follows the ICodingAgentDeployer interface
Before proceeding, the following information must be known. If any of these are unclear or not provided, prompt the user to clarify before starting implementation.
What is the agent's identifier key and display name?
CodingAgent type, CodingAgents record, AGENT_FILE_PATHS, etc.). Examples: opencode, gitlab_duo, continue, agents_md.OpenCode, GitLab Duo, Continue, AGENTS.md.In which directories will Standards be rendered?
.agent/rules/ (one file per standard)AGENTS.md, .agent/guidelines.md (all standards aggregated into one file)In which directories will Commands be rendered?
.agent/commands/).packmind/commands/ as a fallback (same pattern used by GitLab Duo, Junie, and AGENTS.md agents). Users invoke them via @.packmind/commands/command-name.md.In which directories will Skills be rendered?
.agent/skills/CodingAgentArtefactPaths.If standards are rendered into a shared file like AGENTS.md: What should be the precedence rules?
AGENTS.md).RENDER_MODE_ORDER determines priority — agents later in the array supersede agents earlier when both are active.What frontmatter format does the agent require? (YAML, Markdown, plain text, none)
What file extensions should be used? (.md, .mdc, .txt, etc.)
What naming convention should be used for files? (e.g., packmind-standard-{slug}.md, standard-{slug}.mdc)
Does the agent require specific frontmatter properties? (name, globs, alwaysApply, description, etc.)
What is the relative path from agent files to .packmind/standards/ directory?
Convention: Throughout all recipe steps below,
NEW_AGENT/new_agent/NewAgentare placeholders for the identifier key (from prerequisite 1), and'New Agent'is a placeholder for the display name. Substitute both consistently in every step.
Add the new AI agent to the RenderMode enum in packages/types/src/deployments/RenderMode.ts. Add the enum value and include it in the RENDER_MODE_ORDER array to ensure proper ordering. Position matters for supersedence: agents earlier in the array are overridden by agents later in the array when they share a file.
export enum RenderMode {
// ... existing values
NEW_AGENT = 'NEW_AGENT',
}
export const RENDER_MODE_ORDER: RenderMode[] = [
// ... existing values
RenderMode.NEW_AGENT,
];Add the new agent identifier to the CodingAgent union type in both packages/types/src/coding-agent/CodingAgent.ts and packages/coding-agent/src/domain/CodingAgents.ts. Also add it to the CodingAgents record object.
export type CodingAgent =
| 'packmind'
| 'junie'
| 'claude'
| 'cursor'
| 'copilot'
| 'agents_md'
| 'gitlab_duo'
| 'continue'
| 'new_agent';
export const CodingAgents: Record<CodingAgent, CodingAgent> = {
// ... existing values
new_agent: 'new_agent',
};If the agent supports commands, standards, or skills as multi-file artifacts, add it to packages/types/src/coding-agent/CodingAgentArtefactPaths.ts:
MultiFileCodingAgent type unionCODING_AGENT_ARTEFACT_PATHS record for each supported artifact type (command, standard, skill). Use empty string for unsupported artifact types.export type MultiFileCodingAgent = Extract<CodingAgent, 'claude' | 'cursor' | ... | 'new_agent'>;
export const CODING_AGENT_ARTEFACT_PATHS: Record<MultiFileCodingAgent, { command: string; standard: string; skill: string }> = {
// ... existing values
new_agent: {
command: '.new-agent/commands/',
standard: '', // empty if standards are single-file (embedded in a shared file)
skill: '.new-agent/skills/',
},
};Add the agent identifier to the VALID_CODING_AGENTS array in packages/types/src/coding-agent/validation.ts. This enables validation of the agent string in configuration files.
export const VALID_CODING_AGENTS: CodingAgent[] = [
// ... existing values
'new_agent',
];Update the corresponding test in validation.spec.ts to include the new agent in test fixtures.
Add the mapping from RenderMode to CodingAgent in packages/types/src/deployments/RenderModeCodingAgentMapping.ts in the RENDER_MODE_TO_CODING_AGENT record.
export const RENDER_MODE_TO_CODING_AGENT: Record<RenderMode, CodingAgent> = {
// ... existing mappings
[RenderMode.NEW_AGENT]: CodingAgents.new_agent,
};Create a new deployer class in packages/coding-agent/src/infra/repositories/{agentName}/{AgentName}Deployer.ts. Choose a base class based on the agent's rendering pattern:
For hybrid agents (single-file standards + multi-file commands/skills), extend SingleFileDeployer and override the artifact methods:
import { SingleFileDeployer } from '../singleFile/SingleFileDeployer';
export class NewAgentDeployer extends SingleFileDeployer {
// Implement required methods:
// - deployRecipes() - deploy standards/recipes content
// - deploySkills() - deploy skill files to agent directories
// - deployArtifacts() - deploy command files to agent directories
// - generateRemovalFileUpdates() - handle artifact removal
// - generateAgentCleanupFileUpdates() - handle full agent cleanup
}In the deployer, implement frontmatter generation based on the agent's requirements. For Continue-style agents, include name, globs (if scope exists), alwaysApply (false if scope, true otherwise), and description (from summary or standard name). For Cursor-style agents, use simpler frontmatter with just globs and alwaysApply. For single-file agents, frontmatter may not be needed.
// For Continue-style (with name and description)
const frontmatter = standardVersion.scope && standardVersion.scope.trim() !== ''
? `---
name: ${standardVersion.name}
globs: ${standardVersion.scope}
alwaysApply: false
description: ${summary}
---`
: `---
name: ${standardVersion.name}
alwaysApply: true
description: ${summary}
---`;
// For Cursor-style (simpler)
const frontmatter = standardVersion.scope && standardVersion.scope.trim() !== ''
? `---
globs: ${standardVersion.scope}
alwaysApply: false
---`
: `---
alwaysApply: true
---`;Register the new deployer in packages/coding-agent/src/infra/repositories/CodingAgentDeployerRegistry.ts by importing it and adding a case in the createDeployer switch statement. Also add the agent to the canCreateDeployer method.
If the agent supports multi-file artifacts (commands/skills), also add it to the isMultiFileAgent() check if that method exists.
import { NewAgentDeployer } from './newAgent/NewAgentDeployer';
private createDeployer(agent: CodingAgent): ICodingAgentDeployer {
switch (agent) {
// ... existing cases
case 'new_agent':
return new NewAgentDeployer(this.standardsPort, this.gitPort);
default:
// An unreachable switch arm is our bug, not the caller's: PackmindInternalError
// keeps the 500 and the stack, puts `agent` in the log as a field, and withholds
// the message from the response. A bare Error would do none of that.
throw new PackmindInternalError(
'unknown_coding_agent',
{ agent },
`No deployer is registered for coding agent "${agent}".`,
);
}
}
private canCreateDeployer(agent: CodingAgent): boolean {
return (
// ... existing agents
agent === 'new_agent'
);
}Add the new agent to the AGENT_FILE_PATHS record in packages/coding-agent/src/domain/AgentConfiguration.ts. This maps the agent to its main config/standards file path.
export const AGENT_FILE_PATHS: Record<CodingAgent, string> = {
// ... existing mappings
new_agent: 'AGENTS.md', // or '.new-agent/rules/index.md', etc.
};Note: If the agent shares a file path with another agent (e.g., both opencode and agents_md map to AGENTS.md), this is valid but requires supersedence handling in Step 11.
Add the deployer export to packages/coding-agent/src/index.ts so it can be imported by other packages.
export * from './infra/repositories/newAgent/NewAgentDeployer';Skip this step if the agent does not share a config file with another agent.
If two agents write to the same file (e.g., both OpenCode and agents_md write to AGENTS.md), add suppression logic in packages/coding-agent/src/application/DeployerService.ts to ensure only the higher-priority agent writes to the shared file when both are active.
This typically involves:
aggregateStandardsDeployments() and aggregateArtifactRendering()DeployerService.spec.tsAdd the new agent to the agentToFile record in packages/deployments/src/application/utils/GitFileUtils.ts. This maps the agent to its main file for git operations. If the file path is shared with another agent, the deduplication in fetchExistingFilesFromGit() handles avoiding duplicate fetches.
const agentToFile: Record<CodingAgent, string> = {
// ... existing mappings
new_agent: 'AGENTS.md', // or the agent's main file
};Ensure the relative path from agent files to .packmind/standards/{slug}.md is correct. For files in .continue/rules/ or .cursor/rules/packmind/, use ../../.packmind/standards/. For files at root level like CLAUDE.md, use .packmind/standards/. Adjust based on the actual directory structure.
// For .continue/rules/ or .cursor/rules/packmind/
link: `../../.packmind/standards/${standardVersion.slug}.md`
// For root-level files
link: `.packmind/standards/${standardVersion.slug}.md`Add the agent's directory or file to the detection list in apps/cli/src/application/services/AgentArtifactDetectionService.ts. This allows the CLI to detect whether the agent is already set up in a repository.
const AGENT_ARTIFACT_CHECKS = [
// ... existing entries
{ agent: 'new_agent', paths: ['.new-agent'] },
];Add a corresponding test in AgentArtifactDetectionService.spec.ts.
Add the agent to the CLI's agent configuration in apps/cli/src/infra/commands/config/configAgentsHandler.ts:
SELECTABLE_AGENTS array (alphabetically sorted, Packmind always first/excluded)AGENT_DISPLAY_NAMES record with a human-readable nameexport const SELECTABLE_AGENTS: CodingAgent[] = [
'agents_md', 'claude', 'continue', 'copilot', 'cursor', 'gitlab_duo', 'junie', 'new_agent',
];
export const AGENT_DISPLAY_NAMES: Record<CodingAgent, string> = {
// ... existing entries
new_agent: 'New Agent',
};Add tests in configAgentsHandler.spec.ts confirming the agent is in SELECTABLE_AGENTS and has the correct display name.
Add a parser entry for the agent in apps/cli/src/application/utils/parseStandardMd.ts:
AGENT_PARSERS record. For single-file agents that embed standards in a shared file (e.g., AGENTS.md), use () => null since individual standards can't be parsed from the file.DEPLOYER_PARSERS.// In AGENT_PARSERS
export const AGENT_PARSERS: Partial<Record<CodingAgent, (content: string) => ParsedStandard | null>> = {
// ... existing entries
new_agent: () => null, // single-file agent, cannot parse individually
};
// In DEPLOYER_PARSERS (only for multi-file standard agents)
export const DEPLOYER_PARSERS = [
// ... existing entries
{ pattern: '.new-agent/rules/packmind-', parse: parseNewAgentStandard },
];Add the new agent to apps/frontend/src/domain/deployments/components/RenderingSettings/RenderingSettings.tsx by adding entries to RENDER_MODE_TO_VALUE, VALUE_TO_RENDER_MODE, and DEFAULT_FORMATS arrays.
const RENDER_MODE_TO_VALUE: Record<RenderMode, string> = {
// ... existing values
[RenderMode.NEW_AGENT]: 'new-agent',
};
const VALUE_TO_RENDER_MODE: Record<string, RenderMode> = {
// ... existing values
'new-agent': RenderMode.NEW_AGENT,
};
const DEFAULT_FORMATS: RenderingItem[] = [
// ... existing formats
{ value: 'new-agent', name: 'New Agent', checked: false },
];Add the new agent label to apps/frontend/src/domain/deployments/components/RunDistribution/RunDistributionBody.tsx in the renderModeLabels record.
const labels: Record<RenderMode, string> = {
// ... existing labels
[RenderMode.NEW_AGENT]: 'New Agent',
};Add the new agent label to apps/frontend/src/domain/deployments/components/DeploymentsHistory/DeploymentsHistory.tsx in the formatNames record.
const formatNames: Record<RenderMode, string> = {
// ... existing labels
[RenderMode.NEW_AGENT]: 'New Agent',
};Add the new agent to the documentation:
apps/doc/docs/manage-ai-agents.mdx - Add a row to the agent support table showing file locations and supported featuresapps/doc/docs/artifact-rendering.mdx - Add the agent to the standards, commands, and/or skills tables as applicable| **New Agent** | AGENTS.md + `.new-agent/` directories | Yes |Create comprehensive unit tests in packages/coding-agent/src/infra/repositories/{agentName}/{AgentName}Deployer.spec.ts. Follow Packmind test standards: single expectation per test, assertive titles (no "should"), and nested describe blocks for workflows. Test:
describe('NewAgentDeployer', () => {
describe('deployRecipes', () => {
describe('when deploying recipes', () => {
it('creates one file update', async () => {
// Single expectation test
});
});
});
});Create integration tests in packages/integration-tests/src/coding-agents-deployments/{agent-name}-deployment.spec.ts following the pattern of existing integration tests (e.g., cursor-deployment.spec.ts). Test the full deployment workflow through DeployerService, including file creation, frontmatter validation, and content verification. If the agent shares a file with another agent, test the dual-active supersedence scenario. Follow test standards with single expectations and nested describe blocks.
describe('New Agent Deployment Integration', () => {
describe('when deploying standards', () => {
it('creates the expected file', async () => {
// Test through deployerService
});
});
});© PackmindHub, Apache-2.0. 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 packages/.agents/skills/adding-ai-agent-rendering-system of PackmindHub/packmind.
Open the folder on GitHubat commit 8a10541
Adding AI Agent Rendering System 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 |
|---|---|---|---|---|---|---|
| Adding AI Agent Rendering System this skillPackmindHub/packmind | 317 | — | ~4.5k | Automated safety check: Pass | Apache-2.0 | |
| OpenHarness End-to-End EvalsHKUDS/OpenHarness | 16k | 1 repos | ~2.1k | Automated safety check: Notes | MIT | |
| Doc ScreenshotsWordPress/wordpress-playground | 2k | — | ~1.8k | Automated safety check: Pass | GPL-2.0 | |
| Drive MiMo CodeXiaomiMiMo/MiMo-Code | 14k | — | ~3.9k | Automated safety check: Pass | MIT | |
| Plugin Testingpolyipseity/obsidian-terminal | 948 | — | ~828 | Automated safety check: Pass | AGPL-3.0 | |
| Create Modulecartography-cncf/cartography | 4.1k | — | ~2.5k | Automated safety check: Pass | Apache-2.0 |
HKUDS/OpenHarness
Validates OpenHarness features by running real multi-turn agent loops with live LLM calls against an unfamiliar codebase, checking actual tool execution.
WordPress/wordpress-playground
Annotate UI screenshots with documentation callouts in Fellyph's established visual style — uniform-width orange arrows with white halos, double-stroke target outlines, numbered callout cards, dim…
XiaomiMiMo/MiMo-Code
Lets one MiMoCode process drive another, headless with JSON events or interactively through tmux, to test behavior and visual regressions with parseable evidence.
polyipseity/obsidian-terminal
Skill for testing Obsidian plugin features in this repository.
cartography-cncf/cartography
Author a new Cartography intel module end-to-end (entry point, sync GET/TRANSFORM/LOAD/CLEANUP, declarative data model, integration test, schema docs).
marcus/td
Write integration tests for the td-sync admin API using the TestHarness in internal/api/testharnesstest.go.
PackmindHub/packmind
Produce proof-of-execution demos of the Packmind CLI (packmind-cli) as terminal-styled images (colors and formatting preserved exactly), for embedding in a GitHub PR.
PackmindHub/packmind
Record polished UI demo videos and screenshots of a running web app using Playwright MCP — for client deliverables, release notes, feature walkthroughs, or bug repros.
PackmindHub/packmind
Guide for creating effective skills. An agent skill from PackmindHub/packmind.
PackmindHub/packmind
Audit Packmind end-user documentation (apps/doc/) for broken links, outdated CLI references, non-existent concepts, misleading information, and missing coverage.
PackmindHub/packmind
Execute the implementation plan produced by /feature-spec. An agent skill from PackmindHub/packmind.
PackmindHub/packmind
Review an implemented GitHub issue the way a senior Packmind engineer would — the human-judgment checks that ESLint, the TypeScript compiler, and e2e tests cannot catch (authorization scoping…
Implement a new Packmind AI agent rendering/deployer pipeline (single-file or multi-file) with type and registry wiring, frontend UI/docs updates, and thorough unit/integration tests to reliably…. Adding AI Agent Rendering System is an agent skill from PackmindHub/packmind. Implement a new Packmind AI agent rendering/deployer pipeline (single-file or multi-file) with type and registry wiring, frontend UI/docs updates, and thorough unit/integration tests to reliably support additional coding assistants and distribution formats when introducing a new agent integration or render mode.
Adding AI Agent Rendering System fits situations like: tasks that involve Frontend development; tasks that involve Integration testing.
Run `npx skills add PackmindHub/packmind --skill adding-ai-agent-rendering-system -a claude-code`. Or copy the skill folder (packages/.agents/skills/adding-ai-agent-rendering-system in PackmindHub/packmind) into .claude/skills/adding-ai-agent-rendering-system in your project. Claude Code loads it when a task matches its description.
Run `npx skills add PackmindHub/packmind --skill adding-ai-agent-rendering-system -a codex`. Or copy the skill folder (packages/.agents/skills/adding-ai-agent-rendering-system in PackmindHub/packmind) into .agents/skills/adding-ai-agent-rendering-system 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 PackmindHub/packmind --skill adding-ai-agent-rendering-system -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/adding-ai-agent-rendering-system, .gemini/skills/adding-ai-agent-rendering-system, .github/skills/adding-ai-agent-rendering-system and .opencode/skills/adding-ai-agent-rendering-system in your project.
SKILL.md names no scripts, command-line tools or credentials: Adding AI Agent Rendering System 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.
Adding AI Agent Rendering System is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.5k tokens (SKILL.md is roughly 18k 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 Adding AI Agent Rendering System: OpenHarness End-to-End Evals (HKUDS/OpenHarness, 16k stars), Doc Screenshots (WordPress/wordpress-playground, 2k stars), Drive MiMo Code (XiaomiMiMo/MiMo-Code, 14k stars) and Plugin Testing (polyipseity/obsidian-terminal, 948 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
PackmindHub (a GitHub organization) maintains it in PackmindHub/packmind, which has 317 GitHub stars. The repository holds 35 skills in this directory. The repository was last updated on October 8, 2026.
Source: PackmindHub/packmind on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.