# How the OpenCode Skill Execution Model Functions in agent-skills > Understand the OpenCode skill execution model in agent-skills. It automatically discovers selects and executes skills by detecting user intent and invoking the skill tool. - Repository: [Addy Osmani/agent-skills](https://github.com/addyosmani/agent-skills) - Tags: internals - Published: 2026-04-16 --- **The OpenCode skill execution model in addyosmani/agent-skills automatically discovers, selects, and executes appropriate skills by detecting user intent and invoking the `skill` tool against structured [`SKILL.md`](https://github.com/addyosmani/agent-skills/blob/main/SKILL.md) files.** The addyosmani/agent-skills repository implements a skill-driven execution architecture that transforms natural language requests into structured development workflows. This OpenCode skill execution model eliminates manual slash commands by automatically mapping user intent to predefined skills stored in the `skills/` directory, following strict lifecycle rules defined in [`AGENTS.md`](https://github.com/addyosmani/agent-skills/blob/main/AGENTS.md). ## How the OpenCode Skill Execution Model Works The execution model follows a six-step pipeline defined in [`AGENTS.md`](https://github.com/addyosmani/agent-skills/blob/main/AGENTS.md) and [`docs/opencode-setup.md`](https://github.com/addyosmani/agent-skills/blob/main/docs/opencode-setup.md). Each step ensures that user requests translate into predictable, reproducible skill executions. ### Step 1: Intent Detection When a user submits a request, the agent scans the input to determine if any skill applies—even with minimal probability. According to [`AGENTS.md`](https://github.com/addyosmani/agent-skills/blob/main/AGENTS.md) (lines 49-52), the system determines if any skill applies "even [with] 1% chance," ensuring broad pattern matching for feature requests, bug fixes, and other development tasks. ### Step 2: Skill Discovery All available skills reside in the `skills//SKILL.md` structure. As documented in [`docs/opencode-setup.md`](https://github.com/addyosmani/agent-skills/blob/main/docs/opencode-setup.md) (lines 48-55), the system discovers skills by reading markdown files from this directory tree. Each [`SKILL.md`](https://github.com/addyosmani/agent-skills/blob/main/SKILL.md) file contains the full specification for that skill's behavior and workflow. ### Step 3: Automatic Skill Invocation Once the agent identifies a matching skill, it automatically invokes the `skill` tool with the detected skill name. The [`opencode-setup.md`](https://github.com/addyosmani/agent-skills/blob/main/opencode-setup.md) documentation (lines 56-60) specifies that the agent must "Detect when a skill applies → Invoke the `skill` tool," handling the transition from intent recognition to execution without user intervention. ### Step 4: Enforced Workflow Execution Each skill enforces a strict lifecycle that the agent must follow. The [`AGENTS.md`](https://github.com/addyosmani/agent-skills/blob/main/AGENTS.md) file (lines 51-53) mandates that agents "Follow the skill workflow strictly," ensuring standardized execution across different skill types. Workflows typically progress through phases like specification, planning, building, verification, review, and shipping. ### Step 5: Lifecycle Mapping to Implicit Commands The model maps implicit lifecycle commands to concrete skill implementations. As defined in [`AGENTS.md`](https://github.com/addyosmani/agent-skills/blob/main/AGENTS.md) (lines 32-44), commands such as `DEFINE`, `PLAN`, `BUILD`, `VERIFY`, `REVIEW`, and `SHIP` automatically trigger specific skills like `spec-driven-development` or `planning-and-task-breakdown`. This mapping eliminates the need for users to remember specific slash commands. ### Step 6: No Manual Command Requirements Users never type explicit slash commands like `/spec` or `/plan`. The [`opencode-setup.md`](https://github.com/addyosmani/agent-skills/blob/main/opencode-setup.md) documentation (lines 73-74) emphasizes that "The user does **not** need to explicitly request skills," making the interface conversational rather than command-driven. ## OpenCode Skill Execution Examples The following examples demonstrate how the model processes different request types using the `skill` tool and enforced workflows. ### Feature Development Request When a user requests new functionality, the execution model automatically triggers the incremental implementation workflow. ```text User: Add authentication to this app ``` **Agent execution flow:** 1. **Detect intent** → Matches the *feature* pattern in [`AGENTS.md`](https://github.com/addyosmani/agent-skills/blob/main/AGENTS.md). 2. **Select skill** → Chooses `incremental-implementation` from the `skills/` directory. 3. **Run skill** → Executes the `skill` tool, loading [`skills/incremental-implementation/SKILL.md`](https://github.com/addyosmani/agent-skills/blob/main/skills/incremental-implementation/SKILL.md). 4. **Follow workflow** → Progresses through spec → plan → implementation → tests → verification → review → ship. ### Bug Fix Request For debugging scenarios, the model selects appropriate recovery skills. ```text User: Fix the crash when opening settings ``` **Agent execution flow:** 1. Detects *bug-fix* intent from the natural language input. 2. Selects `debugging-and-error-recovery` from available skills. 3. Calls `skill debugging-and-error-recovery` via the built-in tool. 4. Executes the prescribed debugging workflow: reproduce → isolate → fix → test → verify. **Note:** The actual `skill` calls are handled by OpenCode's built-in tool; no manual shell commands are required from the user. ## Key Configuration Files Understanding the OpenCode skill execution model requires familiarity with these specific files in the repository: - **[`AGENTS.md`](https://github.com/addyosmani/agent-skills/blob/main/AGENTS.md)** — Core definition of the OpenCode integration, containing intent-to-skill mapping rules and the execution model specification (lines 32-53). - **[`docs/opencode-setup.md`](https://github.com/addyosmani/agent-skills/blob/main/docs/opencode-setup.md)** — Practical implementation guide describing skill discovery mechanics and automatic invocation protocols (lines 48-74). - **`skills//SKILL.md`** — Individual skill specifications that the `skill` tool loads and executes (e.g., `incremental-implementation`, `debugging-and-error-recovery`). - **`skills//scripts/*.sh`** — Optional bash scripts implementing concrete actions for specific skills, such as test runners or build commands. ## Summary - The **OpenCode skill execution model** automatically bridges natural language requests and structured development workflows in the agent-skills repository. - **Intent detection** runs continuously, checking if any skill applies to user input with even minimal probability. - Skills are discovered from **`skills//SKILL.md`** files and invoked automatically via the **`skill`** tool. - The model enforces a **strict workflow lifecycle** (spec → plan → build → verify → review → ship) without requiring manual slash commands. - **Lifecycle mapping** converts implicit commands like `DEFINE` and `BUILD` into concrete skill executions defined in [`AGENTS.md`](https://github.com/addyosmani/agent-skills/blob/main/AGENTS.md). ## Frequently Asked Questions ### How does OpenCode determine which skill to execute? OpenCode scans user input to detect intent patterns defined in [`AGENTS.md`](https://github.com/addyosmani/agent-skills/blob/main/AGENTS.md), checking if any skill applies even with a minimal probability threshold. When a match is found, the agent automatically selects the corresponding skill from the `skills/` directory and invokes it via the `skill` tool without requiring explicit user confirmation. ### Are manual slash commands required to trigger skills? No. According to [`docs/opencode-setup.md`](https://github.com/addyosmani/agent-skills/blob/main/docs/opencode-setup.md) (lines 73-74), users do not need to explicitly request skills or type slash commands like `/spec` or `/plan`. The agent handles skill invocation automatically through the `skill` tool based on natural language intent detection. ### What is the difference between [`AGENTS.md`](https://github.com/addyosmani/agent-skills/blob/main/AGENTS.md) and individual [`SKILL.md`](https://github.com/addyosmani/agent-skills/blob/main/SKILL.md) files? [`AGENTS.md`](https://github.com/addyosmani/agent-skills/blob/main/AGENTS.md) defines the core execution model, intent detection rules, and lifecycle mapping for the OpenCode integration. Individual [`SKILL.md`](https://github.com/addyosmani/agent-skills/blob/main/SKILL.md) files (located in `skills//`) contain the specific implementation details, workflows, and execution steps for each particular skill. ### Can developers add custom skills to the OpenCode execution model? Yes. Developers can create new directories under `skills//` containing a [`SKILL.md`](https://github.com/addyosmani/agent-skills/blob/main/SKILL.md) file and optional scripts in a `scripts/` subdirectory. The automatic discovery mechanism described in [`docs/opencode-setup.md`](https://github.com/addyosmani/agent-skills/blob/main/docs/opencode-setup.md) will detect these new skills as long as they follow the established directory structure and markdown format.