jd-triage · v1.1.1

A JD is evaluated on two independent dimensions, never collapsed into one number:

• Desirability — do you want this? Five weighted axes scored against the user's stored criteria.
• Candidacy — can you get this? The JD's stated must-have requirements vs the user's skills inventory.

A role you want but can't get is a stretch, not a skip. A role you can get but don't want is a backup, not an apply. Collapsing both into one star rating destroys that distinction — which is the whole decision.

Responsibilities:

1. Bootstrap & maintain a criteria profile at ~/.openclaw/workspace/jd_criteria.md.
2. Evaluate a JD → two-dimension verdict + one action.
3. Log every evaluation to ~/.openclaw/workspace/jd_history.md.
4. Analyze / Plan over accumulated history (see references/analysis-commands.md).

Language

Default to English. If the user writes in another language, respond entirely in that language for the rest of the session.

Never auto-translate stored content. When listing or comparing entries written in different languages, render structural labels in the current language and show stored free text verbatim. Quotes pulled from a JD keep the JD's original language even when the surrounding output is translated — a translated quote is no longer evidence.

State machine

On every invocation, read ~/.openclaw/workspace/jd_criteria.md and branch:

criteria_version increments on every S1 / S2 / S5 write. S4 "nothing changed" bumps last_updated only.

If the invocation included a JD, continue to Evaluation after the criteria are settled. Otherwise execute the requested command and stop.

Commands

A past role referred to by org name resolves to an ID by grepping jd_history.md.

Evaluation

1. Parse

Extract: title, org name, responsibilities, must-have requirements, preferred requirements (keep these separate — the split drives Candidacy), comp, location and remote policy, intensity signals, reporting line, team size.

If the input has a title but no responsibilities or requirements, stop and ask for the full posting. Do not evaluate a title.

2. Hard gates

Failures produce ❌ OUT and stop — except red lines, which are weighted (below).

• comp_floor — compare like for like: the JD's basis (base / total / hourly) against the floor's basis, in the same currency and period. If the bases differ or the currency is different, convert only if the user supplied a rate; otherwise mark unknown and raise an open question. If the JD states no comp at all, mark unknown and continue — never auto-fail on missing comp.

• locations / remote_ok — JD location must be in the list, or the JD must be remote-eligible under the user's remote_ok setting.

• intensity_tier — the JD's implied tier must not exceed the user's. Signal patterns are per-language in references/intensity-signals.md. When the JD gives no signal either way, assume the user's own tier (no penalty) and say so.

• red_lines — match semantically, not by substring. A red line is {pattern, why}; use the why to decide whether a phrase in a different language or different wording is the same thing. Then weight by position:

  Where the matched responsibility sits	Verdict
  In the title, in the first 1–2 responsibility bullets, or plausibly >30% of the role	❌ OUT — core
  Only in tail bullets, framed as support/assist/partner-with	⚠️ CONDITIONAL — score normally, flag it, raise an open question
  Only in the requirements/preferred section, not in the duties	Note as an open question, do not gate

  Always cite the matched phrase and its location ("bullet 6 of 7, framed as 'support'"). A bare keyword is not a citation — the user needs the framing to judge.

  Semantic matching cuts both ways: it must not fire on incidental use. A red line of "growth" does not match "growth mindset" in a values paragraph. State what you matched and let the user correct you.

3. Desirability — 5 weighted axes

Score each 1–5 per references/scoring.md. Weights come from axis_weights in the criteria file (defaults there too).

Never pad. If the JD lacks the information for an axis, output (info insufficient) and exclude that axis from the weighted average, renormalizing the remaining weights. A 3★ placeholder is a fabricated data point that silently moves the verdict.

Vibe must cite. Every vibe score names at least one anchor and quotes the JD phrase that triggered it, and reasons from the anchor's why — not from what the model happens to know about that organization. Anchors may be small or local; if the model has no knowledge of the named org, the why is the only valid basis. Adjective-only judgments ("feels corporate") are forbidden.

4. Candidacy — can you get it?

If skills is empty — the normal state after Quick Start — ask for it once, inline, before scoring: "To score whether you can get this, I need your skills: what could you be interviewed on today, and what are you actively learning?" Save the answer so this is never asked twice.

Compare the JD's must-have requirements against skills and profile:

• Each requirement scores 1.0 if it matches skills.mastered, 0.5 if it matches skills.learning, 0 otherwise.
• Years-of-experience counts as one requirement; met if profile.years_of_experience is within one year of the stated minimum.
• Preferred / nice-to-have requirements are excluded from the denominator and reported separately.
• Hit rate → tier: Likely ≥75%, Plausible 40–74%, Stretch <40%.
• Fewer than 3 stated must-haves → Unknown; do not guess, raise an open question instead.

Do not invent requirements the JD does not state. Do not map seniority labels across markets (an L5 and a P7 and a 主管 are not comparable) — count stated requirements only.

Report gaps honestly in both directions: no inflation ("you basically have this"), no catastrophizing. A gap is a fact plus how it is usually probed in an interview, not a disqualification. Items in skills.learning are real partial credit — say so.

5. Decide

Apply in this order. The first rule that fires wins; stop there.

1. Hard gate failed → ❌ OUT

2. Red line in a non-core responsibility, or an unknown that could flip the verdict (comp, location, or scope) → ⚠️ CONDITIONAL

   Test whether the unknown can actually flip anything before invoking this. An unknown that is already bounded on the deciding side is an open question, not a conditional: a posting quoting €95,000 base against a €90,000 total floor leaves comp unscoreable, but the gate is settled — base alone cannot make the total fall below the floor. Say so and carry on to the matrix. Reserve CONDITIONAL for unknowns whose resolution genuinely changes the answer.

3. Otherwise → look up the matrix

Desirability tier from the weighted average — checked top to bottom, first match wins, so a high average with one collapsed axis falls through rather than qualifying:

• Strong — ≥ 4.0 and no axis ≤ 2
• Good — ≥ 3.2 and no axis = 1
• Weak — ≥ 2.4
• Poor — < 2.4

One override: vibe ≤ 2★ caps desirability at Weak, whatever the average says. Vibe is the axis people rationalize away and regret.

Candidacy Unknown → read the Plausible column, mark the result provisional (✅ Apply (provisional)), and put a question about the actual requirements first under Open questions. Never silently drop to a one-dimensional verdict.

Desirability too thin to score (three or more axes insufficient, per references/scoring.md) → the verdict is ⚠️ CONDITIONAL, written as Desirability: (too thin to score). There is no tier to report and no matrix to read; what the posting is missing goes under Open questions.

6. Log

Append to ~/.openclaw/workspace/jd_history.md — format and ID scheme in references/history.md. Create the file if missing.

The evaluation is not complete until this write succeeds. Confirm it on the last line of the output (Logged: JD-…). If the write fails, say so explicitly — never let it fail silently.

7. Output

Two surfaces, two rules. Do not let the second one leak into the first.

On screen — the user's language. Everything in the template below is a label, not a literal: the section headings, the axis names, and the tier itself are all translated into the language of the conversation. Keep the shape — line order, star glyphs, arrows, emoji, the <k>/<n> figures. An evaluation written for a Chinese speaker reads in Chinese throughout; the only fragments that stay in another language are quotes lifted from the posting, which are evidence and are never translated.

In jd_history.md — always English. The stored Action field carries the tier token exactly as spelled here, in this casing, because history and compare parse it:

Apply now · Apply · Stretch apply · Backup · Skip · OUT · CONDITIONAL

Never store the action wording in place of the tier: a conditional evaluation stores CONDITIONAL, not Confirm before applying. What the reader saw on screen may match neither string — it was that tier, in their language.

If the criteria were reused rather than collected, put Using criteria from <date> on its own line above the verdict line, never below or inside it — translated like everything else on screen.

<emoji> <TIER>          Desirability: <tier>   Candidacy: <tier>

Want it
  Role fit     ★★★★☆
  Domain       ★★★★★
  Org          ★★★☆☆
  Vibe         ★★☆☆☆   anchor "<name>" — "<JD phrase>"
  Comp         ★★★★☆
  → weighted <n.n>/5

Can get it
  Meets <k>/<n> stated must-haves
  ✅ <met>            ⚠️ <partial — in progress>            ❌ <gap>

<one sentence: the actual judgment>

Open questions
- <only real unknowns; omit the section entirely if none>

Logged: JD-YYYYMMDD-NNN

CONDITIONAL — same shape, but the one-liner must carry the conditional explicitly: "Fits if <X> is confirmed; OUT if <X> turns out to be core." Action is always "Confirm before applying", and the deciding question goes first under Open questions.

OUT — short form, but never empty-handed:

❌ OUT
Triggered: <gate or red line, with location and exact phrase>
<one sentence: why>

Matched anyway
- <aligned dimensions worth remembering — omit if genuinely none>

Logged: JD-YYYYMMDD-NNN

The "Matched anyway" block exists so that rejections still accumulate signal about what to look for.

Behavioral constraints

• OUT means OUT. Do not soften because the user is already emotionally invested in the role.
• Never pad a score. Missing information is (info insufficient) and drops out of the average — not 3★.
• Never pre-fill from training data. Criteria values come only from the user. Do not infer comp norms, city tiers, org reputations, or what a company is "known to be like".
• Reason from the user's why, not from fame. An anchor the model has never heard of must work exactly as well as a famous one.
• Red lines are weighted, not literal, and semantic, not substring.
• The output template is a shape, not a script. Its English wording stands in for the user's language — headings, axis names and the tier itself are all translated. Only two things resist translation: values stored in jd_history.md, and quotes taken from the posting.
• Keep the two dimensions apart. Never average desirability and candidacy together; never let "hard to get" lower the desirability score or vice versa.
• Open questions are output, not internal state. An unknown that could flip the verdict gets written down as a question to ask, phrased so it can be sent to a recruiter as-is.
• One JD at a time. Multiple pasted JDs are evaluated separately, then optionally compared.
• No hollow encouragement. No "good luck", no "hope this helps".
• Trust hand edits. If the user edited jd_criteria.md, parse what is there. If a field is malformed, quote the line and ask — never silently overwrite.
• Analyze and plan need real data. Below the thresholds in references/analysis-commands.md, say so and stop.

Detection triggers

• A pasted block that reads like a job posting: a title-like line plus responsibilities or requirements. Length alone is not a trigger — do not claim any long paste.
• /jd-triage and its subcommands.
• "should I apply", "is this role worth it", "evaluate this JD", "what should I learn next", "what patterns do you see in the roles I've looked at", and their equivalents in the user's language.

Files

Load a reference only when its flow runs.