Evaluate the quality of GROWI's suggest-path output by judging each proposed save-path as o (usable) / โณ (usable but improvable) / x (not usable) for a document, with a wiki-agnostic plausibility rubric โ NOT by matching one "correct" path. For each document it reads the wiki content (page bodies, not just path strings), judges each candidate against THIS wiki's own organization, AND drills down the tree to build the document's own ideal home so a candidate is only ruled x once a better place is known (multiple candidates may be usable โ the correct place is not unique). Use it to score suggest-path's proposals as a reviewer would โ e.g. "evaluate suggest-path on this document", "score / check / review these path suggestions", "are these save paths usable", "how good is suggest-path for this wiki", or when dogfooding suggest-path and you want a per-candidate verdict instead of eyeballing it. Trigger it even when the user only says "check"/"score"/"review" suggest-path results without the word "evaluator".
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Evaluate the quality of GROWI's suggest-path output by judging each proposed save-path as o (usable) / โณ (usable but improvable) / x (not usable) for a document, with a wiki-agnostic plausibility rubric โ NOT by matching one "correct" path. For each document it reads the wiki content (page bodies, not just path strings), judges each candidate against THIS wiki's own organization, AND drills down the tree to build the document's own ideal home so a candidate is only ruled x once a better place is known (multiple candidates may be usable โ the correct place is not unique). Use it to score suggest-path's proposals as a reviewer would โ e.g. "evaluate suggest-path on this document", "score / check / review these path suggestions", "are these save paths usable", "how good is suggest-path for this wiki", or when dogfooding suggest-path and you want a per-candidate verdict instead of eyeballing it. Trigger it even when the user only says "check"/"score"/"review" suggest-path results without the word "evaluator".
GROWI's suggest-path takes a document body and proposes parent paths to save it under.
This skill reviews each proposal and marks it โ (usable) / โณ (usable but a better
place exists) / ร (not usable), and โ because a candidate can only be ruled out once
you know where the document should live โ it also drills down the wiki to build the
document's own ideal home and reports it (including "this is a new path" when nothing fits).
It is a measurement/tuning tool for suggest-path, not part of the production feature; it does
not modify suggest-path or GROWI.
The evaluation paradigm: plausibility domain, not answer-key
The correct save location is not unique. A meeting-note could reasonably live under a
minutes tree OR a dev-log tree OR a "discussion" area under an API-spec โ all are legitimate.
So this skill does not pick one canonical answer and grade against it. Instead it asks of
candidate: Multiple โ's are expected and correct.
each
"is placing this document here reasonable, and is there a clearly better
home?"
The drilldown (Phase B) builds a recommended home, but that home is a reference, not a
single must-match key: it tells you when a candidate is beaten (โ โณ with the better place
named), never that a candidate must equal it. This is the deliberate middle ground โ explore
enough to know when a candidate is beaten, without collapsing the answer to one point.
โ โ The non-negotiable constraint: wiki-agnostic
This skill is used on an unknown wiki (wiki-agnostic). It must not be optimized to any
one wiki (= overfitting).
The same kind of document may correctly live in very different places depending on the wiki โ
a spec might sit at /docs/spec/, or root-level /spec/, or /project/<name>/spec/. All
are correct โ only the filing convention differs. The job is: given THIS wiki's own
organization, is placing this document at this candidate path reasonable, and is there a
clearly better home? โ never does it match a specific canonical tree?
Hard rules that follow:
Never encode specific path strings or directory names into the judgement. Reason from
structure, not from memorized paths. The moment a concrete path becomes a fixed criterion,
this becomes a single-wiki tool.
Infer the wiki's classification system from the tree itself (the candidate tree and what
you see while drilling down), then judge whether the document's character fits it. Example:
if this wiki keeps separate trees for different document kinds (specs vs manuals vs minutes),
respect that separation โ but the criterion is "respect the separation THIS wiki makes",
not any particular directory name being canonical.
The judgement stance
Aim to draw the boundary of plausibility, not to hit one narrow correct answer.
Clear mis-placement โ ร. (meeting-notes vs a UI-design tree = obviously different.)
Reasonably plausible โ โ, and be generous: multiple candidates can be โ.
(meeting-notes could sit under a minutes tree OR a dev-log tree OR a "discussion" area under
an API-spec โ all โ.)
Right direction but a clearly better home exists โ โณ (usable, but improvable). โณ is not
a hedge โ it means "you could file it here, but the drilldown found a place that fits
better; here it is." Always pair a โณ with that better place.
Genuinely ambiguous content gets a wider โ, not a forced single pick. ("a meeting where
an API spec was discussed" may belong under minutes or under a spec-discussion area โ allow
both โ.) But "put an API definition into the meeting-minutes tree" โ ร.
The judgement principles (wiki-agnostic)
Transferable reasoning, no fixed path strings. The ordering matters: the firm axes are
applied decisively; the soft axis (depth) must not be applied rigidly โ there, lean โ/โณ,
not ร.
Firm axes โ apply decisively
Clear mis-placement is ร โ this is the core job. A candidate whose subject or
document-kind plainly does not belong (meeting-notes proposed under a UI-design tree; an API
definition under a minutes tree) is ร with confidence. The "obvious no" is the most reliable
verdict this skill makes โ spend your confidence here.
"Usable" = you would actually file it here, not merely "same broad genre". Genre match
alone is not enough; it must be a place a careful person would actually choose.
Personal/private areas are ร for shared content (a candidate under someone's personal
user space, for content that should be a shared wiki asset). It won't become a shared asset
there.
Classification-axis mismatch is ร even if the topic matches. If the document's kind
(spec / manual / minutes / decision-record / โฆ) conflicts with the candidate's
classification โ even when the subject name matches perfectly โ it is ร. Read this
abstractly: "if THIS wiki separates document kinds, a candidate in the wrong kind is ร",
NOT "a specific pair of directory names is canonical". First determine what kind of document
this is, then check the candidate's place is consistent with that kind, as THIS wiki
expresses kinds. (Reading page content, per Phase A, is what lets you catch a
kind-mismatch that the path name alone hides โ and avoid a false ร when the path name looks
wrong but the content fits.)
Soft axis โ do NOT be rigid
Depth is a soft call โ when a candidate is right in subject/kind but arguably one level
off, lean โ/โณ, never ร. Depth is genuinely ambiguous: a careful person filing the same
document twice may not even nest it the same way. So:
Too shallow โ โ (or โณ). A parent broader than ideal still leaves room to nest later;
not fatal as long as subject/kind direction is right. Decide โ vs โณ by THIS wiki's habit
(Phase A step on shallow candidates, below): if siblings under the candidate are organized
into per-topic subdirectories, a too-shallow candidate is โณ (a new subdir is the better
home โ name it in the โณ note); if the area is run flat, it is โ. (Only a catch-all
top-level bucket that anything falls into is too vague โ ร, and that's really axis 1/2,
not depth.)
Too deep โ usually โ, not ร. A slightly-narrower box is a soft miss. Mark
deep-but-on-topic candidates ร only when the box is clearly narrower than the
document's whole scope (a doc about a feature in general, proposed under one sub-detail of
that feature). When it's a judgement call, lean โ/โณ. Do not manufacture strictness.
Tie-breakers
Multiple โ's are expected. If several parents are reasonable, mark them all โ; do not
force a single best.
"When in doubt, ร" applies to KIND/subject doubt, not depth doubt. If you're unsure
because the subject or document-kind might not fit (axes 1โ4), lean ร. If you're unsure only
about how deep an otherwise-fitting candidate sits (axis 5), lean โ/โณ.
Inputs
The document body (required) โ one document, or several for a batch.
The wiki to evaluate against โ which GROWI instance is the tree/ground truth (the same
instance suggest-path is called against). Default: the local GROWI in the devcontainer.
The user does not pre-run suggest-path; this skill calls it.
The flow
For a single document, run Phase A and Phase B against the same wiki, then report. Phase B
runs for every document โ it is what lets Phase A say ร with confidence (you only rule a
candidate out once you know a better place exists).
Step 0. Get suggest-path's proposals
Call suggest-path with the document body. Prefer the MCP tool; fall back to HTTP.
MCP (preferred):mcp__growi__suggestPath with { body: <document> }.
Keep every proposal, including obviously-wrong ones โ the job is to mark each, not to
pre-filter. The path field is what you judge. The description is suggest-path's own
justification โ do not let it sway you; judge body ร path on your own. If suggest-path returns
zero proposals, record that as a result (nothing to mark usable), do not silently skip.
Note on the wiki source. Both phases read the wiki tree and page content through a
Vault interface โ see references/tree-source.md for how to source it today and the
Vault boundary to preserve. Judge content fit, not path-string similarity: a path can
string-match a surface word yet be the wrong home (exactly suggest-path's own failure mode).
Phase A โ judge each candidate โ / โณ / ร
For each proposed parent path:
Understand the document's meaning (subject + kind) from the body.
Decompose the candidate path into its hierarchy, and look at each level's page:
Page has a body โ use that level's content (a snippet is enough) to tell what kind of
page it is.
Box page ($lsx()-only / empty / non-existent intermediate โ a grouping page) โ its
body says nothing; look at its children (titles + snippets) to learn what the box is
for. In GROWI, parent directories tend to be $lsx()-only; the box's identity is told by
its contents, not its own body. A large share of candidate levels are such boxes, so this
is the common case, not the exception. Without reading children you cannot judge a box; do
not guess from its path name.
A path/title can look wrong while the content fits (or vice versa) โ reading the snippet is
what catches kind-mismatches (axis 4) and prevents false ร.
Score the candidate on its own merits (do not overturn it just because Phase B found
somewhere else โ Phase B informs โ-vs-โณ, not the candidate's intrinsic fit):
whole path fits in subject and kind โ โ
part of the path is off but it's still a usable home โ โณ, and name the better place
shallow candidate (right direction, but the wiki would normally nest one level
deeper): look at the candidate's children to read THIS wiki's habit โ per-topic
subdirectories โ โณ (a new subdir is the better home); flat area โ โ. Not a blanket
rule; depends on how organized this part of the wiki is.
subject/kind clearly wrong (any depth) โ ร
Self-consistency gate (below) so you prove you judged THIS document.
Self-consistency gate: prove you judged the right body
Write a one-line body digest: subject + 3โ5 proper nouns / feature names taken verbatim
from the body ({ "subject": "...", "key_terms": ["...", ...] }). Then verify every key term
actually appears in the body you read. If a term you "remember" isn't in the text, you
summarised a different document โ discard, re-read this body, redo Phase A. This catches the
most damaging batch error: filing the right reasoning under the wrong document. It needs
only the body (no answer key), so it works on any wiki and leaks no ground truth.
scripts/reconcile-digests.ts runs this check mechanically over a batch (see Batch mode).
Phase B โ drilldown to the document's ideal home (always run)
Build, from the wiki, where this document should go. This is the reference that lets Phase A
distinguish โ from โณ (and rule ร with confidence). It is a beam descent from the root:
From the root, at each level:
a. List the level's children (titles + snippets).
b. Pick the candidates worth descending into โ the "plausible" children, up to 3
(keep a child whose snippet fits even if its title looks marginal; don't drop on title alone
โ that's how a good-but-oddly-named home gets missed).
c. Read the full body of those kept children (up to 3) and choose the best fit to
descend into. Don't commit to one child on a single glance โ that prunes a better branch too
early.
d. Stop when no child fits the document better than the current node โ the current
node is the recommended save location. Depth cap 5 levels as a backstop and cycle guard;
the real stop is "no better child", not the cap. Most save locations are far shallower than
5, so the cap rarely bites โ note it if you hit it.
If nothing along the descent fits, conclude "new path" and state where it would hang.
"Better fit" is a judgement call you make (LLM judgement) โ do not reduce it to a
numeric threshold; thresholds invite the arbitrariness this skill exists to avoid.
Phase A and Phase B share work: in both you read a node's children to understand the wiki's
granularity habit. Do it once and reuse it โ the box-identity reads in Phase A step 2 and the
child-listing in Phase B are the same kind of access.
Cost caveat. Reading up to 3 full bodies per level can add up on deep trees. Listing
children with short snippets is cheap; the full-body reads are the cost to watch. Run the
defaults above (beam โค3, full-reads โค3, depth โค5) on a few cases first, measure the real
cost, and retune the beam/depth if needed. Don't assume it's free.
Step 4. Report
Per document:
## <document label>
- Body digest: <subject> | key terms: <term, term, ...> (self-consistency check; all terms must be in the body)
- This wiki's inferred organization: <one line: how it separates kinds / nests topics>
- suggest-path proposals, each judged:
1. <path> โ โ | โณ | ร โ <one-line why: which principle; for โณ, the better place>
2. <path> โ โ | โณ | ร โ ...
- Recommended home (Phase B drilldown): <path, or "new path under <parent>">
- Usable count: <#โ+#โณ> / <#candidates> (โ: <#โ>, โณ: <#โณ>, ร: <#ร>)
- Note: <where suggest-path went wrong, or why a call was hard / genuinely ambiguous>
โณ always carries its better place โ either a sibling/child path the drilldown found, or
the Phase B recommended home.
The Phase B recommended home appears once per document (not per candidate); a candidate
may equal it (โ that candidate is โ), be beaten by it (โ โณ), or be unrelated (judge on its own
axes).
Do not emit absolute point scores (they drift run-to-run). The โ/โณ/ร marks are the output;
aggregate them across documents (below) for rates.
Batch mode and per-domain rates
A single document is the core unit. For a batch, run the flow per document, then aggregate.
Batches are where bodies get swapped โ gate every document (Phase A's self-consistency gate
is mandatory in batch mode; a body that fails reconciliation is a suspected swap: re-judge it in
isolation before it enters the aggregate; reconciliation is a deterministic string check, not
another LLM pass). scripts/reconcile-digests.ts runs this gate over a directory of bodies and
exits non-zero on a suspected swap, so it can block aggregation.
Aggregate from the โ/โณ/ร marks (scripts/aggregate.ts turns per-document verdicts into the
per-domain table):
usable-rate (case-level) โ fraction of documents with โฅ1 usable (โ or โณ) candidate. This
is a precision-side number: "did suggest-path put at least one reasonable place in its
list". It cannot measure recall (whether a good place existed that suggest-path never
proposed) โ but Phase B's recommended home gives a recall signal: count cases where the
recommended home matched no proposed candidate (= suggest-path missed a better place it
should have offered). Report both, and label the usable-rate as precision-side.
per-candidate โ/โณ/ร rates โ fraction of all candidates in each class.
ร-concentration by reason โ group ร's by which principle triggered them (clear
mis-placement / axis-mismatch / personal-area / vague-catch-all). Different reasons point at
different suggest-path fixes. Depth is, by design, rarely a ร here.
Group by whatever "domain" fits the batch (wiki area, document type). If you bound coverage
(sampled docs, capped the proposal list, hit the depth cap), say so โ a silent cap reads as
"measured everything".
On the verdict unit (why โ/โณ/ร and not hit/miss)
The โ/โณ/ร verdict is deliberately a plausibility judgement, not an answer-key match. A
human reviewing the same proposals marks candidates the same way โ so this skill's output can
be sanity-checked by a human reading a handful of cases. Two things to keep in mind when doing
that:
The human's marks are a useful reference but not absolute truth: a human marks candidates
one by one, while this skill, seeing the whole tree via Phase B, may know a better home the
human overlooked. So human-โ / skill-โณ (and vice versa) is expected, not a bug โ the two
will not agree perfectly, and shouldn't be forced to.
If the skill ever needs tuning, fix disagreements only by sharpening the wiki-agnostic
principles above โ never by adding concrete paths to make one wiki's numbers look better
(that helps one wiki and breaks every other).
References
references/tree-source.md โ how to source the wiki tree and page content today (the
current adapter and the Vault-interface boundary to preserve). Phase A (box-identity reads)
and Phase B (beam descent) both go through it.
scripts/reconcile-digests.ts โ deterministic self-consistency gate for batch mode (every
key term in a document's digest must appear in that document's body; exits non-zero on a
suspected body-swap).
scripts/aggregate.ts โ aggregates per-document โ/โณ/ร verdicts into the per-domain table
(usable-rate, per-candidate โ/โณ/ร rates, recall-miss rate from Phase B, and an ร-by-reason
breakdown). Input is a JSON list of per-document records (candidates + an optional
recommended_home_in_candidates recall flag); see the script's header for the shape.
