Fresh eyes review
Fresh-eyes review of a changeset by a fresh-context agent — catches regressions and correctness issues the authoring context reads past.From its SKILL.md
npx -y skills add eai-org/agent-toolkit --skill fresh-eyes-reviewAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its file declares
Copied from the file, not written here
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
4.2 KB, as published. Nobody here has run it
Fresh-eyes review
A context that produced a change reads its intent, not its text, so same-context review misses what a fresh reader would catch. The fix is procedural: a reviewer whose context holds only the artifacts.
Workflow
- Resolve the inputs. The changeset: whatever the invocation names — a branch, a commit, a diff range, a draft vs its original. Given none, infer it from the session — usually the work just finished, committed or not; no VCS required. With no session context to draw on, fall back to the current git diff; when that too yields nothing, ask the user what to review. Pin the changeset as concretely as the environment allows — a diff or commit range where one exists, otherwise the touched files, with their prior state when reconstructable. Alongside it, a short statement of what the change is supposed to achieve, when one exists (the task as stated, a PR or ticket description); when this session authored the change, never include the session's own reasoning, plan, or messages — leaked rationale recreates the blindness the fresh context exists to remove. Done when changeset and intent are pinned down and free of authoring context.
- Confirm the prompt. Assemble the reviewer prompt — changeset, intent, the mandate and exclusions below, and any further reviewer instructions the invocation supplies (e.g. what to report back). When the invocation supplied changeset, intent, and mandate explicitly (e.g. a driving skill), nothing was inferred, so skip the confirmation and proceed. Otherwise show the prompt to the user verbatim and wait for approval; fold any doubt about an inferred changeset into the proposal rather than asking separately. Text emitted before a tool call may not be displayed, so never show the prompt and then ask via a question tool in the same turn — end the turn with the prompt and a plain-text ask, or embed the prompt in the question tool. Done when the user has approved the prompt, as shown or amended — or the explicit-inputs skip applied.
- Spawn one fresh-context reviewer (a subagent or equivalent isolated session) with the prompt, free to read any surrounding project material — except the paths the prompt lists as excluded: any exclusions the invocation supplies, plus, when this session authored the change, session-authored files that are not part of it (plans, notes, scratch), since a fresh context cannot tell them apart. Its mandate, unless the invocation redirects it (e.g. security only): regressions and correctness, including contradictions with surrounding code, rules, or docs — though matching surrounding code is not correctness: verify any pattern the change extends or mirrors is itself sound, since completing a broken rollout inherits its breakage; ambiguities a reader without context would trip on; and, when an intent statement was given, whether the change does what it says. Tough but grounded, aimed at mistakes that matter: every finding names its location and a concrete failure scenario; style nits, speculation, and padding are out of scope, and zero findings is a valid outcome. Out of scope bounds what is reported, never what is investigated: a pre-existing anomaly in the mechanism the change touches is a reason to audit it. If the harness cannot isolate a context, fall back to an adversarial pass over the same inputs in the main session. Done when an isolated reviewer has returned its findings, or the fallback pass ran and its result is flagged as same-context (weaker).
- Report back. Relay every finding intact — location and failure scenario included — plus whatever else the reviewer was instructed to return; add the session's own assessment when useful, but never silently drop or soften a finding. What to do with the findings is the caller's decision, not this skill's. Done when every reviewer finding appears in the report.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.
Gives 0 of the 12 instructions most review quality skills give
Counted across 1,273 of the 2,403 authors here whose files we hold, read 2026-09-06
- Ask one question at a timein 63 of 1273, across 62 files
- Provide a recommended answer for each questionin 47 of 1273, across 45 files
- Rank findings by severityin 44 of 1273
- Use parameterized queries for database accessin 38 of 1273, across 20 files
- Validate all user input with schemasin 33 of 1273, across 15 files
- Store secrets in environment variablesin 32 of 1273, across 14 files
- Explore the codebase to answer questionsin 31 of 1273, across 29 files
- Store tokens in httpOnly cookiesin 30 of 1273, across 12 files
- Implement rate limiting on API endpointsin 30 of 1273, across 12 files
- Sanitize user-provided HTMLin 29 of 1273, across 11 files
- Return generic error messages to usersin 28 of 1273, across 10 files
- Cite file and line for every findingin 28 of 1273, across 25 files
Said here and by no other author read
- Resolve changeset and intent from session or user
- Exclude session-authored plans and notes from review
- Mandate review for regressions and correctness
- Verify soundness of patterns extended by changes
- Require location and failure scenario for every finding
- Report all findings intact without softening
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.