Agent Skills: Portable Contract and Runtime Boundary

A skill is not a long prompt with a better filename. It is a discoverable package of instructions, resources, and executable helpers that enters an agent's context through a runtime contract.

Type: Build Languages: Python (stdlib) Prerequisites: Phase 13 · 01 (The Tool Interface), Phase 13 · 05 (Tool Schema Design) Time: ~90 minutes

Learning Objectives

• Define an agent skill without confusing it with a prompt, repository instructions, a tool, a hook, a subagent, or a plugin.
• Read the portable SKILL.md contract and separate it from runtime-specific extensions.
• Explain discovery, selection, activation, resource loading, tool use, and verification as distinct lifecycle stages.
• Validate a skill package before a runtime places it in an agent's catalog.
• Choose between a skill, MCP tool, hook, subagent, or ordinary code for a concrete task.

Ten-Minute First Success

Do this before the long explanation. You will create a small skill, install the complete reviewer bundle into a real agent host, invoke it, verify the result, and remove it. This proves the lifecycle with an observable result.

Preflight for the real-host lab

The real-host checkpoint requires Node.js, npx, Python 3, one selected skill-capable host, and write access to the project or user scope you choose in the installer. Verify the local commands first:

node --version
npx --version
python3 --version

Decide which host and scope you will use before installation. If any requirement is unavailable, read this lesson on the website or continue with the manual package exercise below. That fallback teaches the contract, but it does not prove host discovery, invocation, bundled-script execution, or uninstall behavior. Keep those observations marked pending.

1. Start in an empty working directory

Run these commands from any parent directory where you keep learning work:

mkdir -p agent-skills-first-run
cd agent-skills-first-run
TARGET_ROOT="$(pwd -P)"
printf 'TARGET_ROOT=%s\n' "$TARGET_ROOT"
ls -A

The final command should print nothing. If it prints files, choose a different empty directory so the review has a clear boundary.

Create a directory for your first skill:

mkdir -p my-first-skill

Create my-first-skill/SKILL.md with this content:

---
name: my-first-skill
description: Turn rough meeting notes into a compact decision record when the user asks to capture a technical decision.
---

# Decision record

Extract the decision, context, alternatives, owner, and next review date.
If the notes do not contain a decision, ask one clarifying question instead
of inventing one.

Verify that you created the file in the intended directory:

test -f my-first-skill/SKILL.md

No output and exit code 0 means the file exists.

2. Install the complete reviewer bundle

Stay in agent-skills-first-run and run:

npx skills add rohitg00/ai-engineering-from-scratch --skill skill-contract-reviewer --full-depth

Choose the agent host and scope you are using. The installer should list skill-contract-reviewer and the destination it wrote. --full-depth is required because this lesson's skill is a nested bundle with references, a script, and an asset.

Set SKILL_ROOT to the absolute directory reported by the installer. It must be the directory containing the installed SKILL.md, not the lesson source directory and not the current workspace:

# Replace the placeholder with the destination printed by the installer.
SKILL_ROOT="$(cd "/absolute/path/to/skill-contract-reviewer" && pwd -P)"
test -f "$SKILL_ROOT/SKILL.md"
printf 'SKILL_ROOT=%s\n' "$SKILL_ROOT"

If the agent session was already open, start a new session or use that host's skill rescan command. Do not assume every host hot-reloads its catalog.

3. Invoke it explicitly

In the installed agent, with agent-skills-first-run as the working directory, use the syntax supported by that host:

Use the absolute values printed for SKILL_ROOT and TARGET_ROOT in the request. Require the host to expand them before execution and show the exact resolved command, not a command that depends on the process working directory:

Use skill-contract-reviewer to review <TARGET_ROOT>/my-first-skill. The installed bundle root is <SKILL_ROOT>. Run python3 <SKILL_ROOT>/scripts/check_skill.py <TARGET_ROOT>/my-first-skill. Before running it, show the fully resolved argv. Return the validation report, selected primitives, and one sentence for each selection. Include the resolved script path, resolved target path, cwd, argv, and exit code as execution evidence.

The resolved command should have this shape, with no placeholders remaining:

python3 "/absolute/install/path/skill-contract-reviewer/scripts/check_skill.py" \
  "/absolute/workspace/path/agent-skills-first-run/my-first-skill"

A successful result has all three properties:

1. The host finds skill-contract-reviewer by name.
2. The reviewer reads the package contract and runs its bundled validator.
3. The response contains a validation report with no structural error for the sample, plus a justified primitive selection.

The execution evidence must also name the script path, target path, cwd, exact argument vector, and exit code. A fluent report without those fields does not prove that the installed companion script ran.

If the host reports that the skill is unavailable, verify the install destination, rescan or restart once, and retry the explicit request. Do not rewrite the skill description to hide an installation failure.

4. Probe implicit selection

Start a fresh agent turn and enter the same task without naming the skill:

Review <TARGET_ROOT>/my-first-skill as a reusable agent package and tell me whether its package contract is valid.

If the host exposes selected skills, record whether it chose skill-contract-reviewer. If the host does not expose routing, mark implicit selection as unverified. The explicit invocation is the portable fallback.

5. Clean up

Remove only the installed reviewer bundle:

npx skills remove skill-contract-reviewer

Select the same host and scope used during installation. After a rescan or new session, an explicit request for skill-contract-reviewer should report that it is unavailable. Keep my-first-skill for the later lessons, or remove the lab directory after you finish the track.

The Problem

Suppose your team has a reliable release workflow. It finds merged changes, checks migration notes, updates the changelog, runs a packaging command, and produces a review checklist.

Putting that workflow in one prompt makes it easy to paste and hard to operate. The prompt has no stable identity, no discovery rule, no resource boundary, no testable package shape, and no answer to basic questions: Who may invoke it? When should the model select it? Which scripts can it run? Which files are trusted? What survives when context is compacted?

The opposite mistake is to treat every reusable instruction as a skill. Repository conventions, deterministic automation, external tools, event hooks, and delegated agents solve different problems. Packing all of them into SKILL.md produces a directory that looks portable while depending on one host's undocumented behavior.

The first engineering task is classification. Decide what the artifact is before you decide how to package it.

The Concept

Skills encode procedural knowledge

An agent skill is a directory whose entry point is SKILL.md. The entry file contains YAML frontmatter followed by Markdown instructions. The directory can also contain references, scripts, and assets.

The directory, not the Markdown file alone, is the deployable unit. A copied SKILL.md with missing references is a broken package even if its frontmatter parses.

The neighboring abstractions

A release skill can tell the agent how to inspect a release. An MCP server can expose the release registry. A hook can forbid direct pushes. A subagent can independently audit the candidate. These pieces compose because they keep different responsibilities.

The word "skill" names two different ideas

Research systems sometimes call a learned program, successful trajectory, or environment-specific policy fragment a skill. An agent can create these artifacts during exploration, retrieve them by task similarity, execute them, and revise the library from feedback. Phase 14 · 10 builds that kind of lifelong-learning library.

An Agent Skill in this mini-track is different. It is an authored package with a declared filesystem contract, catalog metadata, progressive disclosure, runtime-mediated invocation, and host-controlled tools. It can be generated or improved by an agent, but learning is not required for the format.

Both ideas package reusable competence. They should not share implementation claims merely because they share a name.

The portable core

The Agent Skills specification requires two frontmatter fields:

---
name: release-readiness
description: Inspect a release candidate when the user asks whether a version is ready to publish.
---

name is the stable identifier. It must satisfy the specification's naming rules and match the parent directory. description is both documentation and routing metadata. It should say what the skill does and when it applies.

The portable optional fields are:

The Markdown body holds the operational instructions. It should define the workflow, decision points, failure behavior, and direct paths to supporting resources.

# Release readiness

Use this workflow for a release candidate, not for ordinary development builds.

1. Read `references/release-policy.md`.
2. Run `python3 scripts/inspect_release.py --format json`.
3. Stop if the report contains a blocking failure.
4. Produce the checklist from `assets/release-checklist.md`.
5. Ask for approval before any publish or tag action.

Runtime extensions are a second layer

Some hosts accept extra frontmatter or companion configuration. Those fields can be useful, but they are not automatically portable.

Treat each extension as an adapter. Keep the core workflow valid without it, document the fallback, and test the host that consumes it. A runtime may ignore an unknown field, reject it, or preserve it without implementing the behavior.

Frontmatter is executable metadata

Metadata changes system behavior before the skill body is read.

• A malformed name can make discovery fail.
• A vague description can route the wrong requests.
• A human-only flag can remove the skill from the model's catalog.
• A tool allowance can change whether a host asks for permission.
• A context setting can move execution into a separate agent session.

Review frontmatter like configuration code. Validate it, version it, and include its behavior in evals.

The skill lifecycle

Each arrow is a boundary with its own failure modes.

1. Discovery finds possible packages in configured locations.
2. Validation rejects malformed or unsafe packages before catalog publication.
3. Cataloging exposes a compact name and description, not the full package.
4. Selection decides whether the skill is relevant.
5. Activation loads the body into model-visible context.
6. Disclosure reads references or assets only when a branch requires them.
7. Execution uses host tools under the host's permission and isolation rules.
8. Verification checks the produced artifact independently of the model's claim.

Collapsing these stages causes bad mental models. A discovered skill is not active. An active skill is not authorized to do everything it describes. A permitted tool call is not proof that the result is correct.

Skills and tools are orthogonal

MCP answers, "Which capabilities can this application call, and what are their schemas?" A skill answers, "How should an agent approach this class of task?"

The skill may name a tool, but the host owns the actual capability registry. If the tool is absent, the skill should state a fallback or fail clearly. It should never imply that naming a capability creates it.

Skills and repository instructions are different scopes

Repository instructions describe the environment you are already in: commands, conventions, generated files, and boundaries. A skill provides reusable procedure for a task that may occur across many repositories.

When both apply, the active user request and repository rules constrain the skill. A generic refactoring skill must not override a repository rule that forbids editing generated files.

Skills do not import one another

One skill can direct the agent to invoke another, but this is not a language-level import. The second skill still goes through runtime discovery, eligibility, activation, permissions, and context handling.

Write cross-skill dependencies as observable workflow edges:

After producing the candidate changelog, invoke the `release-risk-review` skill.
Pass the candidate path and require a blocking or non-blocking verdict.
If that skill is unavailable, stop and report the missing dependency.

This makes the dependency testable and gives the host a chance to enforce policy.

Build It

code/main.py implements a small standards-oriented validator and an artifact chooser. It stays stdlib-only so every rule is visible.

The validator exposes:

• parse_frontmatter(text) to separate metadata from the body.
• validate_skill_text(text, directory_name, allowed_runtime_extensions=()) to check required fields, naming, unknown extensions, body presence, and portable limits.
• ValidationIssue and SkillReport to return structured evidence instead of one opaque boolean.
• FrontmatterSyntaxError for input that cannot be interpreted safely.

The chooser exposes TaskShape and select_primitives(task). It maps a task's needs to ordinary code, repository instructions, a skill, a hook, a subagent, or an MCP tool.

Run the lab:

cd "$(git rev-parse --show-toplevel)"
cd phases/13-tools-and-protocols/22-skills-and-agent-sdks
python3 code/main.py
python3 -m unittest discover -s code/tests -v

This command block requires a local clone and must start from anywhere inside that clone so git rev-parse --show-toplevel can resolve the repository root.

The demo prints JSON for one valid portable skill, one host-extended skill, one invalid package, and several task-shape decisions. Inspect the issue codes. A package validator should explain how to fix an artifact without guessing on the author's behalf.

Validation order matters

Validate cheap structural facts before deeper content rules:

This order prevents secondary errors from obscuring the first broken invariant.

Use It

Before writing a skill, fill out this decision card:

Many production workflows use more than one row. The card prevents one artifact from pretending to provide every property.

Ship It

This lesson produces the skill-contract-reviewer bundle under outputs/. It contains:

• a portable SKILL.md that reviews a proposed skill package;
• reference checklists for the portable contract and primitive selection;
• a deterministic validation script;
• task-shape fixtures covering prompts, skills, tools, hooks, ordinary code, and subagents.

Install the full bundle, not only its entry file:

cd "$(git rev-parse --show-toplevel)"
python3 scripts/install_skills.py /tmp/aiefs-skills --phase 13 --type skill

The course installer reports each copied Phase 13 skill and writes /tmp/aiefs-skills/manifest.json. This clean destination checks package shape; the first-success loop above checks discovery and invocation in a real host.

The following lessons deepen each lifecycle stage. Lesson 24 builds discovery and progressive disclosure. Lesson 25 builds invocation policy and routing. Lesson 26 separates permissions from sandboxing. Lesson 27 turns the whole package into an evaluated release artifact.

Exercises

1. Classify five workflows from your own team using TaskShape. Defend every case where you choose more than one primitive.
2. Add boundary tests proving that a 500-character compatibility value passes and a 501-character value fails as a specification error.
3. Add one runtime extension to the allowlist. Write a test proving the same file is still distinguishable from a portable-only skill.
4. Split a 400-line prompt into SKILL.md, one reference, one script contract, and one output template. Keep every file responsible for one kind of information.
5. Design a failure response for a skill that references an unavailable MCP tool. Do not silently substitute a tool with broader permissions.
6. Review an existing skill and label every sentence as routing, procedure, policy, reference pointer, or output contract. Move anything that does not belong.

Key Terms

Further Reading

• Agent Skills specification for the portable directory and frontmatter contract.
• Agent Skills best practices for scope, instructions, and resource organization.
• OpenAI: Build skills for current Codex discovery and invocation behavior.
• Claude Code skills for one runtime's invocation, argument, tool, and delegated-context extensions.