# Skillsaw Ecosystem Scout > Survey the AI coding assistant and agentic tool ecosystem, assess skillsaw's competitive position, identify emerging patterns and missing capabilities, and produce a prioritized strategic report as a GitHub issue. - **Type:** Skill - **Install:** `agentstack add skill-stbenjam-skillsaw-skillsaw-ecosystem-scout` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [stbenjam](https://agentstack.voostack.com/s/stbenjam) - **Installs:** 0 - **Category:** [Developer Tools](https://agentstack.voostack.com/c/developer-tools) - **Latest version:** 0.1.0 - **License:** Apache-2.0 - **Upstream author:** [stbenjam](https://github.com/stbenjam) - **Source:** https://github.com/stbenjam/skillsaw/tree/main/.opencode/skills/skillsaw-ecosystem-scout - **Website:** https://skillsaw.org/ ## Install ```sh agentstack add skill-stbenjam-skillsaw-skillsaw-ecosystem-scout ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # skillsaw Ecosystem Scout You are conducting a strategic assessment of the AI coding assistant and agentic tool ecosystem. Your goal is to identify what skillsaw should support next to maximize open-source adoption and mindshare. This skill produces **analysis, not code**. The output is a GitHub issue with a structured report and prioritized recommendations. ## Step 1: Catalog skillsaw's current capabilities Before looking outward, establish what skillsaw does today by reading the codebase: - `src/skillsaw/rules/builtin/__init__.py` — full list of builtin rules - `src/skillsaw/context.py` — supported repository types - `README.md` — feature set (linting, scaffolding, doc generation, CI action) - `.skillsaw.yaml.example` — full config surface - `src/skillsaw/marketplace/cli.py` and `src/skillsaw/marketplace/add.py` — scaffolding capabilities Summarize: what formats does skillsaw validate? What can it scaffold? What specs does it track? What repository types does it detect? ## Step 2: Discover and survey the AI coding assistant ecosystem Use WebSearch to find the current landscape. Do not rely on a hardcoded list of tools — the ecosystem changes fast. Run searches like: - "AI coding assistant tools {current year}" - "AI coding assistant plugin format" - "AI coding assistant rules configuration" - "AI coding assistant marketplace registry" - "new AI coding assistants {current year}" - "agentic coding tools open source" Follow up on each significant tool you find. Fetch their documentation with WebFetch and identify configuration/skill/plugin formats. For each tool discovered, record: 1. What configuration file formats does it use? 2. Does it have a concept of skills/plugins/extensions? 3. Does it have a marketplace or registry? 4. Does it support MCP? What MCP-related configuration? 5. What validation or linting exists for its formats (if any)? 6. How large/active is the community? (star counts, contributor activity, downloads) Cast a wide net. The goal is to discover tools and formats skillsaw does not yet know about, not just to check the ones it already supports. ## Step 3: Survey competing linters, scaffolding tools, and developer tooling skillsaw is a linter, scaffolder, and doc generator. Search for anything that overlaps with or competes against these capabilities: - "AI coding assistant linter" - "AI agent config validator" - "cursor rules linter" - "MCP server linter validator" - "AI coding assistant scaffolding tool" - "AI agent plugin generator scaffold" - "AI rules file generator" - "dotfiles linter AI assistant" For each competing tool found, determine: - What does it lint, validate, or scaffold? - What formats does it support? - How mature is it? (GitHub stars, npm/pip downloads, last commit date) - What does it do that skillsaw does not? - What does skillsaw do that it does not? - Is it gaining traction or stalled? Also look for adjacent developer tooling that could inform skillsaw's roadmap: IDE extensions, CLI tools, CI actions, or registries that serve the same ecosystem. ## Step 4: Survey agent protocols and emerging standards Use WebSearch to discover what protocols and standards are gaining traction: - "agent communication protocol standard {current year}" - "agent-to-agent protocol" - "MCP server registry validation" - "AI agent interoperability standard" - "agentic AI configuration format standard {current year}" - "skill sharing format AI agents" For each protocol or standard found, determine: - What is it? Who is behind it? - How mature is it? (spec draft, stable, widely adopted) - Does it define file formats or configuration that a linter could validate? - Is adoption growing or stalled? Look for convergence trends — are multiple tools adopting the same formats? Are there interoperability initiatives emerging? ## Step 5: Identify user pain points and unmet needs Search for what problems developers are actually hitting and asking for help with. Look at forums, discussions, and issue trackers: - "AI coding assistant rules not working" - "cursor rules best practices" - "claude code plugin problems" - "MCP server configuration issues" - "AI agent skill debugging" - "managing AI coding assistant config across team" Also search GitHub Issues, Discussions, and Reddit for complaints, workarounds, and feature requests related to AI assistant configuration. Look for patterns: - What do people struggle with when writing rules or plugins? - What breaks when teams share or standardize AI assistant config? - What manual steps do people wish were automated? - What quality or security concerns do people raise about skills/plugins? - Are there common "how do I validate my X?" questions with no good answer? The goal is to find **real demand signals** — problems people are already having that skillsaw could solve. These are higher-value than features nobody asked for. ## Step 6: Assess skillsaw's competitive position Compare the baseline from Step 1 against findings from Steps 2–5. For each ecosystem tool or format, classify as: - **Already supported** — skillsaw validates this today. Note the current rules. - **Partially supported** — skillsaw covers some aspects but is missing fields, features, or format versions. - **Not supported but feasible** — a clear, stable format exists that skillsaw could validate with new rules. - **Not supported and unclear** — the format is too new, unstable, or undocumented for reliable validation. - **No format to validate** — the tool has no configuration format a linter could check. ## Step 7: Identify highest-impact opportunities Rank opportunities by likely impact on open-source adoption. Consider: - **User base size** — how many developers use this tool? Rules for tools with millions of users have more reach than niche tools. - **Format stability** — is the format stable enough to write durable rules? Unstable formats mean maintenance burden. - **Competitive gap** — is skillsaw the only linter that could serve this format? Being first matters. - **Implementation effort** — how much work? A new RepositoryType and rule set vs. a single new rule. - **Cross-format synergy** — does supporting this format benefit existing users? Many repos have both `.cursor/rules/` and `.claude/rules/`. Produce a ranked list of recommended actions, each with: | Field | Description | |-------|-------------| | **What** | The format or capability to add | | **Why** | The strategic rationale | | **Effort** | Low / Medium / High | | **Impact** | Low / Medium / High | | **Depends on** | Any prerequisites | ## Step 8: Check for new primitives and concepts Beyond format validation, look for new categories of capability: - **Skill testing/evaluation** — are there emerging standards for testing skills? - **Skill interoperability** — can skills be shared across tools? Is a universal format emerging? - **Security scanning** — beyond MCP allowlisting, are there security concerns in skill/plugin formats that a linter should catch? - **Dependency management** — emerging patterns for skill dependencies, versioning, or compatibility declarations? - **Agent orchestration config** — new formats for multi-agent workflows? - **Quality metrics** — download counts, ratings, trust signals for skills/plugins? ## Step 9: Produce the strategic report Create a GitHub issue using `gh issue create` with: - **Title:** `[Ecosystem Scout] Strategic Assessment - {YYYY-MM-DD}` - **Labels:** `ecosystem` (create the label if it does not exist) Use this structure for the issue body: ```markdown ## Ecosystem Scout Report **Date**: {date} **skillsaw version**: {version from pyproject.toml} ### Current Capabilities Summary {Brief summary of what skillsaw supports today} ### Ecosystem Landscape #### AI Coding Assistants | Tool | Config Format(s) | Skills/Plugins? | Marketplace? | MCP? | Community Size | skillsaw Support | |------|------------------|-----------------|--------------|------|----------------|------------------| | ... | ... | ... | ... | ... | ... | ... | #### Competing Linters & Tooling | Tool | What it does | Formats | Traction | Gap vs skillsaw | |------|-------------|---------|----------|-----------------| | ... | ... | ... | ... | ... | #### Agent Protocols | Protocol | Status | Relevance to skillsaw | |----------|--------|----------------------| | ... | ... | ... | ### User Pain Points & Unmet Needs {Problems developers are hitting, demand signals from forums/issues/discussions} ### Competitive Assessment {For each tool/format: detailed status and gap analysis} ### Prioritized Recommendations #### High Priority {Ranked list with What / Why / Effort / Impact} #### Medium Priority {Ranked list} #### Low Priority / Watch List {Items to monitor but not act on yet} ### New Primitives & Concepts {Emerging patterns that could inform skillsaw's roadmap} ### Raw Research Notes Detailed findings per tool {Full notes from each tool surveyed} --- Generated by the [skillsaw-ecosystem-scout](https://github.com/stbenjam/skillsaw) skill. ``` ## Step 10 (Optional): Create tracking issues Only if the user explicitly requests it (e.g., via `--create-issues` or by asking in the prompt), create individual GitHub issues for each high-priority recommendation: - **Title:** `[Ecosystem] {brief description}` - **Labels:** `ecosystem` - **Body:** The recommendation details from the report, with a link back to the main assessment issue. Do not create tracking issues unless explicitly asked. ## Important constraints - This skill produces analysis, not code changes. **Never create PRs.** - Use WebFetch for known URLs and WebSearch for discovery. Both are needed. - Be specific — cite URLs, version numbers, star counts, and dates. - Do not recommend adding support for formats that are proprietary, undocumented, or likely to change drastically within months. - If a web fetch fails (site down, URL changed), note the failure and move on. Do not block the entire report on one failed fetch. - Recommendations must be actionable. Bad: "consider supporting more tools." Good: "Add Cursor rules validation (`.cursor/rules/*.mdc` with YAML frontmatter) — Cursor has 2M+ users and no existing linter for this format." ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [stbenjam](https://github.com/stbenjam) - **Source:** [stbenjam/skillsaw](https://github.com/stbenjam/skillsaw) - **License:** Apache-2.0 - **Homepage:** https://skillsaw.org/ Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-stbenjam-skillsaw-skillsaw-ecosystem-scout - Seller: https://agentstack.voostack.com/s/stbenjam - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.