How do I install the Build Agent Harnesses skill?

Run npx skillmds@latest add hiteshbandhu/build-agent-harnesses in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Build Agent Harnesses safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Build Agent Harnesses?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Build Agent Harnesses free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Build Agent Harnesses?

hiteshbandhu (@hiteshbandhu) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Build Agent Harnesses by hiteshbandhu

Name: Build Agent Harnesses
Author: hiteshbandhu

Build Agent Harnesses

Runs checklists and workflows for designing, hardening, and operating agent harnesses — guardrails, verify steps, tool loops, durable sessions, eval, quotas, coding/deep-research/voice harnesses. Use when the user builds agent runtimes, asks what a harness is, scopes agent vs workflow, or says "agent harness", "guardrails", "verify step", "FOMAT", "durable session".

hiteshbandhu Updated Sep 17, 2026

File contents

Build agent harnesses

Action playbook from twenty-two AI Engineer talks on agent & harness engineering. Do not summarize talks — pick a workflow and execute it.

Supporting files (read when needed):

workflows.md — workflows A–L (steps, deliverables, stop conditions)
source-index.md — src-NNN → talk learnings in ingest-into-skills

Optional deliverables: {SKILL_OUTPUT_DIR}/build-agent-harnesses/ — see skills-i-use OUTPUT.md.

Step 0 — Pick workflow

Use the decision tree below. Open the matching section in workflows.md.

What is the user trying to do?
├─ Define harness vs agent loop + guardrails/verify     → A
├─ Decide agent vs workflow for a use case              → B
├─ Maturity path: framework → state machine → scale     → C
├─ Enterprise: quotas, skills, multi-agent platform     → D
├─ Agent evaluation + anti-hype discipline            → E
├─ Long-horizon research / deep research harness        → F
├─ Coding agent / computer-use / IDE harness            → G
├─ Production chat UX: resume, steer, multi-device      → H
├─ Operate many parallel coding agents (FOMAT)          → I
├─ Regulated / domain-vertical knowledge agents         → J
├─ Delete scaffold; maximize LLM compute in backend     → K
└─ Post-training / finetune / RL for tool agents        → L

Stop summarizing once a workflow is identified — run its checklist.

Install

cp -r skills/build-agent-harnesses ~/.claude/skills/
cp -r skills/build-agent-harnesses ~/.cursor/skills/
cp -r skills/build-agent-harnesses ~/.codex/skills/

From skills-i-use or ingest-into-skills after sync.

Source corpus: ingest-into-skills playlists/agent-harness-engineering-ai-engineer/.

Cross-cutting rules

Rule	Source
Harness = tools + context + guardrails + verify around the model	[src-001 @ 4:36]
Do not prompt harder when verify shows failure — fix harness	[src-001 @ 9:37]
Agents only when ambiguity/value/error profile justify cost	[src-002 @ 2:57]
Every agent is a state machine; prune prompts as models improve	[src-003 @ 4:37]
Agent eval needs environments + actions, not I/O strings only	[src-006 @ 7:52]
Decouple clients via durable sessions for resume/steer	[src-015 @ 5:25]

Disputed steps: read talk in source-index.md.

Output to user

Name the workflow (A–L) and what you are producing
Save artifacts under ./skill-outputs/build-agent-harnesses/ when the user wants files
Do not auto-commit

Invocation examples

@build-agent-harnesses design a harness for our browser agent
agent vs workflow for this support bot?
we need quotas and verify steps for production agents

---name: build-agent-harnessesdescription: Runs checklists and workflows for designing, hardening, and operating agent harnesses — guardrails, verify steps, tool loops, durable sessions, eval, quotas, coding/deep-research/voice harnesses. Use when the user builds agent runtimes, asks what a harness is, scopes agent vs workflow, or says "agent harness", "guardrails", "verify step", "FOMAT", "durable session".---# Build agent harnessesAction playbook from twenty-two AI Engineer talks on agent & harness engineering. **Do not summarize talks** — pick a workflow and execute it.**Supporting files** (read when needed):- [workflows.md](workflows.md) — workflows A–L (steps, deliverables, stop conditions)- [source-index.md](source-index.md) — src-NNN → talk learnings in ingest-into-skillsOptional deliverables: `{SKILL_OUTPUT_DIR}/build-agent-harnesses/` — see [skills-i-use OUTPUT.md](https://github.com/hiteshbandhu/skills-i-use/blob/main/skills/OUTPUT.md).---## Step 0 — Pick workflowUse the decision tree below. Open the matching section in [workflows.md](workflows.md).```What is the user trying to do?├─ Define harness vs agent loop + guardrails/verify → A├─ Decide agent vs workflow for a use case → B├─ Maturity path: framework → state machine → scale → C├─ Enterprise: quotas, skills, multi-agent platform → D├─ Agent evaluation + anti-hype discipline → E├─ Long-horizon research / deep research harness → F├─ Coding agent / computer-use / IDE harness → G├─ Production chat UX: resume, steer, multi-device → H├─ Operate many parallel coding agents (FOMAT) → I├─ Regulated / domain-vertical knowledge agents → J├─ Delete scaffold; maximize LLM compute in backend → K└─ Post-training / finetune / RL for tool agents → L```**Stop summarizing** once a workflow is identified — run its checklist.---## Install```bashcp -r skills/build-agent-harnesses ~/.claude/skills/cp -r skills/build-agent-harnesses ~/.cursor/skills/cp -r skills/build-agent-harnesses ~/.codex/skills/```From [skills-i-use](https://github.com/hiteshbandhu/skills-i-use) or ingest-into-skills after sync.Source corpus: [ingest-into-skills](https://github.com/hiteshbandhu/ingest-into-skills) `playlists/agent-harness-engineering-ai-engineer/`.---## Cross-cutting rules| Rule | Source ||------|--------|| Harness = tools + context + guardrails + verify around the model | [src-001 @ 4:36] || Do not prompt harder when verify shows failure — fix harness | [src-001 @ 9:37] || Agents only when ambiguity/value/error profile justify cost | [src-002 @ 2:57] || Every agent is a state machine; prune prompts as models improve | [src-003 @ 4:37] || Agent eval needs environments + actions, not I/O strings only | [src-006 @ 7:52] || Decouple clients via durable sessions for resume/steer | [src-015 @ 5:25] |Disputed steps: read talk in [source-index.md](source-index.md).---## Output to user1. Name the workflow (A–L) and what you are producing2. Save artifacts under `./skill-outputs/build-agent-harnesses/` when the user wants files3. Do not auto-commit---## Invocation examples```@build-agent-harnesses design a harness for our browser agentagent vs workflow for this support bot?we need quotas and verify steps for production agents```

Frequently asked questions