# Dogfood > > - **Type:** Skill - **Install:** `agentstack add skill-ractive-hyalo-dogfood` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [ractive](https://agentstack.voostack.com/s/ractive) - **Installs:** 0 - **Category:** [Productivity](https://agentstack.voostack.com/c/productivity) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [ractive](https://github.com/ractive) - **Source:** https://github.com/ractive/hyalo/tree/main/.claude/skills/dogfood ## Install ```sh agentstack add skill-ractive-hyalo-dogfood ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Dogfood Session A dogfood session exercises hyalo against real knowledgebases to find bugs, verify fixes, assess UX, and discover improvement opportunities. Sessions should feel like a real user working with the tool — not a mechanical checklist. Be curious, follow interesting leads, try edge cases that occur to you naturally. ## Phase 1: Prepare 1. **Build from source**: `cargo build --release` 2. **Find the last dogfood report** to establish the baseline: ```bash hyalo find --tag dogfooding --sort date --reverse --limit 1 --format text ``` Read it to learn: which version was tested, which bugs were found, what was verified. 3. **Discover what changed since then**: Use `git log --oneline` from that report's date to HEAD. Look for merged iteration branches (`iter-N/...`). For each, read the iteration file in the knowledgebase to understand what was implemented: ```bash hyalo find --tag iteration --property "date>=YYYY-MM-DD" --sort date --format text ``` Then `hyalo read --format text` for each to understand the features, bug fixes, and UX changes. These are your priority test targets. 4. **Check prior dogfood reports** for open bugs to re-verify: ```bash hyalo find --tag dogfooding --sort date --reverse --limit 5 --format text ``` Read the most recent reports and collect any bugs marked as found (not yet verified fixed). 5. **Pick target knowledgebases**: Use a mix of: - **Own KB** (`hyalo-knowledgebase/`, ~250 files) — well-structured, has schemas/views - **MDN Web Docs** (`../mdn/files/en-us/`, ~14K files) — large, stress-tests performance - **GitHub Docs** (`../docs/content/`, ~3.5K files) — complex nested YAML frontmatter - **VS Code Docs** (`../vscode/`, ~1K files) — mid-size, different structure For external KBs, check they exist first (`ls ../mdn/files/en-us/ > /dev/null 2>&1`). Create a snapshot index for large vaults (500+ files). ## Phase 2: Exercise the tool This is the creative part. Don't follow a rigid script — think about what a real user would do with hyalo and try it. That said, make sure every session covers these categories: ### New feature verification Test the features you discovered in Phase 1 from the iteration files and git log. For each new feature or changed command, don't just check the happy path — try edge cases, wrong inputs, combinations with other flags. The iteration files describe what was implemented and often include acceptance criteria that suggest good test scenarios. ### Bug regression testing Re-verify bugs from the most recent dogfood report(s). Use the exact commands or scenarios that originally exposed them. Mark each as STILL FIXED, REGRESSED, or PARTIALLY FIXED. ### Creative exploration This is where you go beyond verification. Try things like: - Unusual filter combinations (`--property` + `--tag` + BM25 + `--section`) - Edge-case inputs (empty strings, special characters, very long queries) - Commands on files with unusual frontmatter (nested objects, empty values, unicode) - `--jq` queries to build ad-hoc reports or dashboards - Views that chain with additional CLI flags - `mv` on files with many inbound links - `lint --fix --dry-run` on messy external KBs - Schema validation on write (`--validate` or `validate_on_write`) - Performance comparisons (indexed vs non-indexed, small vs large vault) - `links fix` on KBs with broken links - Anything that occurs to you as you go — follow your curiosity ### UX assessment Pay attention to: - Are error messages helpful? Do they suggest what to do? - Are hints useful and relevant? - Is `--format text` output scannable? - Do help texts match actual behavior? - Any friction points or confusing behavior? ### Performance spot-checks Time a few representative commands on each KB used: ```bash time hyalo find --limit 1 # baseline parse speed time hyalo find "some query" # BM25 search time hyalo summary # full vault scan time hyalo find --property status=completed # structured filter ``` Compare with prior reports if available. Flag regressions > 2x. ## Phase 3: Write the report Save to `hyalo-knowledgebase/dogfood-results/` with this naming and frontmatter: ```yaml --- title: "Dogfood vX.Y.Z — " type: research date: YYYY-MM-DD status: active tags: [dogfooding, ...] related: - "[[dogfood-results/previous-report]]" - "[[iterations/relevant-iteration]]" --- ``` ### Report structure Organize findings into clear sections. Use this general shape, but adapt as needed: ```markdown # Dogfood vX.Y.Z — Brief context: binary version, which KBs tested, file counts. ## New Feature Verification ### Feature Name (iter-NNN) — WORKING / BROKEN / PARTIAL Description of what was tested and results. ## Bug Regression Testing ### BUG-N: Description — STILL FIXED / REGRESSED Commands tested, results observed. ## Bugs Found ### BUG-N: Description (SEVERITY) Steps to reproduce, expected vs actual, impact. ## UX Issues ### UX-N: Description (SEVERITY) What's confusing or could be better. ## What Worked Well Highlight things that are genuinely good — performance wins, helpful errors, etc. ## Performance Table of timings if measured. ``` Severity levels: HIGH (data loss, wrong results), MEDIUM (confusing behavior, workaround exists), LOW (cosmetic, minor friction). ### After writing the report Use `hyalo set` to ensure the frontmatter is correct. Add `related` links to relevant iterations or prior dogfood reports. ## Tips for good dogfood sessions - **Follow the hints.** Hyalo outputs drill-down suggestions — use them like a real user would. - **Don't skip external KBs.** Many bugs only surface at scale or with unusual frontmatter. The own KB is too well-structured to catch everything. - **Note what's NOT there.** Missing features, things you wished you could do — these are just as valuable as bugs. - **Be specific.** Include exact commands, exact error messages, exact output. Vague reports like "search felt slow" aren't actionable. - **Test across KBs.** A command that works on the own KB might fail on MDN due to scale or on GitHub Docs due to nested YAML. - **Check data quality.** Use `lint`, `find --broken-links`, `find --orphan` to surface issues in the KB itself — this is valuable dogfooding too. ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [ractive](https://github.com/ractive) - **Source:** [ractive/hyalo](https://github.com/ractive/hyalo) - **License:** MIT 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-ractive-hyalo-dogfood - Seller: https://agentstack.voostack.com/s/ractive - 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%.