b2a2119984* Add why-and-when doc explaining value proposition and decision guide Adds docs/why-and-when.md covering why skills over MCP matters (same channel as tools, discovery, dynamic updates, control model, multi-server composition, enterprise distribution) and when MCP distribution adds value vs simpler alternatives. Linked from README and problem-statement. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Add why-and-when summary to README before problem statement Gives newcomers the value proposition immediately: skills are context, MCP is a context protocol, and remote MCP servers can serve tools and know-how together. Links to the full doc for depth. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Add portable sub-agent point to why-and-when doc Skills over MCP replaces the pattern of independently wrapping each MCP server in a custom sub-agent with hand-written instructions — the server author ships orchestration guidance once, everyone benefits. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Acknowledge enterprise trust trade-offs in both directions Address PR feedback: git-based and MCP-based skill distribution each raise different governance concerns. Link to open question on security and trust boundaries. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
31 lines
2.4 KiB
Markdown
31 lines
2.4 KiB
Markdown
# Problem Statement
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[Agent Skills](https://agentskills.io/home) support in AI applications demonstrates demand for rich workflow instructions, but there's no convention for exposing equivalent functionality through MCP primitives.
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## Current Limitations
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- **Server instructions load only at initialization** — new or updated skills require re-initializing the server
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- **Complex workflows exceed practical instruction size** — some skills require hundreds of lines of markdown with references to bundled files, scripts, and examples
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- **No discovery mechanism** — users installing MCP servers from a registry don't know if there's a corresponding skill they should also install
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- **Multi-server orchestration** — skills may need to coordinate tools from multiple servers, which doesn't fit the single-server instruction model
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## Broader Context
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Skills discoverability is a specific instance of a more general MCP challenge: context-as-resources discoverability and standardization of client host behavior around non-tool primitives. The ecosystem has largely optimized for tools, and patterns for how clients discover and consume other forms of context — including skills — remain underdeveloped. Solutions in this space are likely to have implications beyond skills alone.
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MCP's value for skills goes beyond distribution; it provides an interaction model. MCP defines app, human, and assistant roles, giving skills a built-in framework for control model decisions (who sees the content, who decides when it loads). This makes MCP a natural complement to skills as a delivery channel for workflow instructions.
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## Key Use Cases
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See [use-cases.md](use-cases.md) for detailed use cases and community input. In summary:
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1. **Complex Workflow Orchestration** — Multi-step workflows requiring 875+ lines of instruction (e.g., [mcpGraph](https://github.com/TeamSparkAI/mcpGraph))
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2. **Conditional Workflows** — Branching instructions dynamically loaded based on context
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3. **Multi-Server Composition** — Skills leveraging tools from multiple off-the-shelf servers
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4. **Progressive Disclosure** — Skills broken into linked file sets, loaded on demand
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## Open Questions
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See [open-questions.md](open-questions.md) for the full list of unresolved questions with community input.
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For the value proposition and a guide on when MCP distribution applies, see [why-and-when.md](why-and-when.md).
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