Strategy — Job search aggressiveness configuration
SkillSearchConfigure and adjust the job search strategy level. The agent interrogates the user, proposes a level, and saves it to DB. All flows respect it.
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Then ask your AI: use the Strategy — Job search aggressiveness configuration skill
What this skill tells your AI
The instructions your AI receives, as published by galiprandi/job-seeker in .agents/skills/strategy/SKILL.md and read by ahel’s review.
Trigger
Keyword: strategy
The user says strategy (or variants: "cambiar estrategia", "change strategy", "more aggressive", "less aggressive", "urgency", "how active") and the strategy configuration flow is triggered.
Purpose
The job search has configurable aggressiveness. Different situations (employed vs unemployed, urgent vs relaxed) require different levels of effort. This flow lets the user define and adjust their strategy, which all other flows respect.
Pre-flight
- Load current strategy:
node scripts/db.js "SELECT value FROM preferences WHERE user_id = 1 AND category = 'workflow' AND key = 'strategy_level' AND status = 'active'" node scripts/db.js "SELECT data->'strategy' AS strategy FROM users WHERE id = 1" - If no strategy exists, note that onboarding step 4b was skipped. Default to
selective.
Flow
1. Show current strategy
If a strategy exists, show the user:
Current strategy: selective
- Apply batch: 5 jobs per session
- Targets batch: 5 companies per session
- Daily frequency: 1x/day
- Match threshold: Must only
- Follow-up: 5 days
- Relax Must-haves: none
- Cold outreach: no
- Active sources: radar, apply, targets, referrals, news
2. Ask about current situation
Present the 4 levels (see AGENTS.md "Strategy levels") and ask:
- ¿Estás empleado actualmente?
- ¿Qué tan urgente es tu búsqueda?
- Sin urgencia, solo mirando →
passive - En los próximos meses, buscando algo mejor →
selective - Necesito algo pronto →
active - Necesito algo ya, desesperado →
aggressive
- Sin urgencia, solo mirando →
- Pregunta adaptativa según career stage (leer
users.data.profile.career_stageyusers.data.profile.has_management):- Si
career_stagees junior/mid: "¿Estás abierto a roles de un nivel más alto al tuyo, o solo a roles de tu mismo nivel?" - Si
career_stagees senior+ yhas_management = true: "¿Aceptarías roles IC o solo Manager?" - Si
career_stagees senior+ yhas_management = false: "¿Te interesa dar el salto a management o prefieres seguir como IC?"
- Si
- ¿Aceptarías hybrid si el proyecto es muy bueno?
- ¿Quieres que aplique automáticamente o solo te muestre opciones?
Nunca preguntes "IC o Manager?" a un usuario junior/mid. La pregunta 3 se adapta al perfil inferido del CV.
Based on answers, propose a level. Explain what changes:
Based on your answers, I propose: active
This means:
- I'll apply to 10 jobs per session (Must + Strong matches)
- Register on 10 target companies per session
- Run daily 2x/day
- Follow up after 3 days instead of 5
- Relax your top 2 Must-haves (the agent resolves which ones from your profile)
- Send cold outreach to recruiters at target companies
Does this work? You can adjust any parameter individually.
3. Allow customization
After proposing a level, let the user customize individual parameters:
- "Quiero que apliques a 15 pero solo Must-matches" → override
apply_batch_size = 15, keepmatch_threshold = must_only - "No quiero cold outreach" → override
cold_outreach = false - "Relajar remote pero no mentorship" → override
relax_must_haveswith specific keys from the user's Must-haves (the agent readsusers.data.job_preferencesto resolve which keys to relax)
4. Save to DB
# Save level
node scripts/db.js "INSERT INTO preferences (user_id, category, key, value, confidence, source) VALUES (1, 'workflow', 'strategy_level', '<level>', 1.0, 'explicit_statement') ON CONFLICT (user_id, category, key) DO UPDATE SET value = EXCLUDED.value, source = EXCLUDED.source, updated_at = NOW()" --write
# Save detailed parameters
node scripts/db.js "UPDATE users SET data = jsonb_set(data, '{strategy}', '<json>'::jsonb) WHERE id = 1" --write
The strategy JSON contains all parameters (see AGENTS.md "Strategy levels"). Example for active with customizations:
{
"level": "active",
"apply_batch_size": 15,
"targets_batch_size": 10,
"daily_frequency": "2x/day",
"match_threshold": "must_strong",
"follow_up_days": 3,
"relax_must_haves": "top_2_must_haves",
"relaxed_keys": ["remote", "salary"],
"cold_outreach": false,
"sources_active": ["radar", "apply", "targets", "referrals", "news"]
}
relax_must_haves stores the strategy level (top_2_must_haves, top_3_must_haves, none). relaxed_keys is the resolved list of actual Must-have keys from users.data.job_preferences that the agent will relax. The agent populates relaxed_keys at runtime by reading the user's Must-weighted preferences and picking the top N by priority.
5. Confirm
Show the final strategy and confirm:
Strategy saved: active (customized)
- Apply: 15 jobs/session, Must+Strong matches
- Targets: 10 companies/session
- Daily: 2x/day
- Follow-up: 3 days
- Relaxed: top 2 Must-haves (remote, salary)
- Cold outreach: disabled
- Sources: radar, apply, targets, referrals, news
All flows will respect this. Say "strategy" again to change it.
Level defaults
See AGENTS.md "Strategy levels" for the full table. Summary:
| Level | apply_batch | targets_batch | daily | match | follow_up | relax | cold |
|---|---|---|---|---|---|---|---|
| passive | 0 | 0 | on-demand | must_only | 7 | none | false |
| selective | 5 | 5 | 1x/day | must_only | 5 | none | false |
| active | 10 | 10 | 2x/day | must_strong | 3 | top_2_must_haves | true |
| aggressive | 15 | all | 2x/day | must_strong_nice | 2 | top_3_must_haves | true |
Rules
- Always show current strategy first before proposing changes
- Explain what changes when proposing a new level. The user needs to understand the impact
- Allow customization of any parameter after choosing a level. Don't force all defaults
- Save both the level name (preferences) and detailed params (users.data.strategy). The level is the quick reference, the params are what flows actually read
- Report what was saved (Gold Rule 3). One line: "Estrategia actualizada: active"
- Never change strategy without asking. Even if memory detects a situation change, propose the change and wait for confirmation
- Single user (repo owner)
Dependencies
- Depends on
onboarding(DB must exist) - Read by all flows at pre-flight
- Memory skill can trigger this flow when situation changes are detected
Timing and batch sizes
Practical limits per session (validated empirically):
- An apply session can process 7-10 Easy Apply jobs in ~30 min
- Connection requests: 8-10 per session (avoid LinkedIn limits)
- Direct emails: 4-5 per session (each takes ~2 min with attachment)
- Effective total per session: 15-20 application/contact actions
- Some companies have very long forms that take ~10 min each. The rest take 2-5 min each
These limits interact with strategy levels:
passive: 0 applications, 0 targets (on-demand only)selective: 5 applications, 5 targets per sessionactive: 10 applications, 10 targets per sessionaggressive: 15 applications, all targets per session
LinkedIn limits: custom notes on connection requests have a weekly cap. When exhausted, send invites without a note. Don't retry with a note.
Signals
- GitHub stars
- 26
- Forks
- 1
- Last commit
- Sep 2026
- Hacker News mentions
- 20
Advanced
- Catalog kind
- skill
- Gateway key
strategy-galiprandi- Source
- github.com/galiprandi/job-seeker