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dogfood-tui

Structured TUI dogfooding and QA workflow using agent-tty. Use for exploratory testing, bug hunting, release-readiness validation, and UX review of terminal applications.

64

Quality

80%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./skill-data/dogfood-tui/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

75%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A strong, disciplined workflow skill: a numbered dogfooding procedure with explicit wait-based validation points, an executable session skeleton, an evidence checklist, an issue taxonomy, and a report template — all in lean, imperative prose. The remaining gaps are minor: no error-recovery loops, placeholder launch command, and slight repetition in the instrument-selection section.

DimensionReasoningScore

Conciseness

The body is dense and imperative with no padding about what TUIs or terminals are; every section (instrument choice, workflow, skeleton, checklist, taxonomy, template) carries non-obvious guidance such as "Treat snapshot --format text as searchable terminal text evidence, not as an authoritative column-width oracle". It sits at anchor 4 rather than 5 because the "Choose the Evidence Instrument" section restates the prefer-source-first point across three paragraphs where one or two would do, and a few checklist lines could be tightened.

4 / 5

Actionability

Concrete commands with flags appear throughout (doctor --json, wait --screen-stable-ms, snapshot --format text --json, record export --format webm --json) and the session skeleton is a nearly copy-paste-ready bash block. It stops short of anchor 5 because the skeleton leaves '<launch-command>' as an undocumented placeholder and steps 4–5 describe run/type/send-keys and wait --text/--idle-ms without a concrete invocation example of each.

4 / 5

Workflow Clarity

The 10-step workflow is clearly sequenced with explicit checkpoints: doctor prerequisites before capture work, "Wait on observable state with wait instead of blind sleeps" with per-condition flags, an evidence checklist, and session teardown. It matches anchor 4 rather than 5 because there are no error-recovery feedback loops (e.g. what to do when doctor fails or the app crashes mid-loop), even though the operations are non-destructive so no cap applies.

4 / 5

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ are absent), so everything lives in a single 113-line SKILL.md with clean, well-ordered section headers and no nested references. Content is appropriately inline for a workflow of this size, matching anchor 4's "good structure; most content is appropriately placed"; it does not reach anchor 5, which expects well-signaled one-level-deep reference files, and at ~113 lines the issue taxonomy or report template could optionally be split out.

4 / 5

Total

16

/

20

Passed

Description

78%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A well-formed description: third-person voice, concise, with an explicit "Use for..." trigger clause covering the main scenarios and both TUI/terminal phrasings. The main residual weakness is that the "what" names activity categories rather than the concrete evidence operations the skill actually performs.

DimensionReasoningScore

Specificity

The description names the domain ("Structured TUI dogfooding and QA workflow") and the tool (agent-tty) plus several specific activities — "exploratory testing, bug hunting, release-readiness validation, and UX review" — which matches the anchor for several specific actions with minor gaps (it does not mention evidence capture like screenshots or session recordings). It falls below anchor 5 because the activities are category names rather than fully concrete operations, and above anchor 3 because coverage goes beyond 1–2 actions.

4 / 5

Completeness

Both parts are present: the what ("Structured TUI dogfooding and QA workflow using agent-tty") and an explicit when ("Use for exploratory testing, bug hunting, release-readiness validation, and UX review of terminal applications"). The when clause is concrete, but the what stays at a fairly abstract level — it does not enumerate the concrete operations (sessions, snapshots, screenshots, recordings) — so it matches anchor 4 rather than anchor 5's fully explicit both-parts example.

4 / 5

Trigger Term Quality

"Use for exploratory testing, bug hunting, release-readiness validation, and UX review of terminal applications" supplies natural phrases users would say, plus both "TUI" and "terminal applications" as synonyms. It sits below anchor 5, which expects exhaustive synonym/extension coverage (e.g. "dogfood this app", "QA the release", "test my TUI"), but clearly exceeds anchor 3's partial keyword coverage.

4 / 5

Distinctiveness Conflict Risk

The niche is clear and narrow — dogfooding/QA of TUIs via agent-tty — and the triggers (TUI, terminal applications, exploratory testing, release-readiness) are unlikely to fire for unrelated skills. This matches anchor 5's "clear niche with distinct triggers; minimal conflict risk"; anchor 4 would require noticeable overlap with a closely related skill, which is not the case.

5 / 5

Total

17

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

coder/agent-tty

Path

skill-data/dogfood-tui/SKILL.md

Reviewed

Table of Contents

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