behavioral-modification
About
This Claude Skill provides force-free behavioral modification techniques for dogs, addressing issues like reactivity, separation anxiety, and resource guarding. It uses systematic methods such as desensitization and counter-conditioning with threshold management. Developers should use it to handle specific, established problem behaviors after basic obedience training.
Quick Install
Claude Code
Recommendednpx skills add pjt222/agent-almanac -a claude-code/plugin add https://github.com/pjt222/agent-almanacgit clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/behavioral-modificationCopy and paste this command in Claude Code to install this skill
Documentation
Behavioral Modification
Unwanted dog behaviors → desensitize, counter-condition, manage env.
Use When
- Reactivity (lunge, bark, growl) at dogs, ppl, stimuli
- Separation anxiety → destruction, vocal, soiling when alone
- Resource guarding: stiff, growl, snap near food/object
- Excessive bark, jump, pull, etc. interfere w/ life
- After basic obedience — builds on foundation cmds
In
- Required: Specific unwanted behavior ("dog lunges at dogs on leash", not "bad")
- Required: Threshold distance or trigger level (close/intense before behavior)
- Optional: History (start, triggers, worsen factors)
- Optional: High-value treats dog eats when mildly stressed
- Optional: Vet clearance (rule out pain/medical)
Do
Step 1: Define Behavior
Precision matters — vague descriptions → vague interventions.
Behavior Analysis (ABC Model):
+-------------+------------------------------------------+
| Component | Define Specifically |
+-------------+------------------------------------------+
| Antecedent | What happens BEFORE the behavior? |
| (Trigger) | e.g., "sees another dog within 30 feet" |
+-------------+------------------------------------------+
| Behavior | What EXACTLY does the dog do? |
| | e.g., "stiffens, stares, then lunges and |
| | barks" |
+-------------+------------------------------------------+
| Consequence | What happens AFTER the behavior? |
| | e.g., "owner pulls the dog away; the |
| | other dog leaves" (behavior is reinforced |
| | because the trigger goes away) |
+-------------+------------------------------------------+
Threshold Mapping:
- At what distance/intensity does the dog first notice the trigger? (alert)
- At what distance/intensity does the dog become unable to take treats? (over threshold)
- The working zone is BELOW threshold — where the dog notices but can still think
→ Precise behavior def + trigger + threshold distance + current consequence.
If err: No consistent trigger → log 1 wk: date, time, ctx, behavior, consequence. Patterns emerge.
Step 2: Pick Strategy
Strategy Selection:
+----------------------------+-----------------------------------+-----------------+
| Behavior | Primary Strategy | Timeline |
+----------------------------+-----------------------------------+-----------------+
| Reactivity (dogs/people) | Desensitization + counter- | 4-12 weeks |
| | conditioning (DS/CC) | |
+----------------------------+-----------------------------------+-----------------+
| Separation anxiety | Graduated absence protocol + | 6-16 weeks |
| | management | |
+----------------------------+-----------------------------------+-----------------+
| Resource guarding | Trade-up protocol + | 4-8 weeks |
| | approach desensitization | |
+----------------------------+-----------------------------------+-----------------+
| Excessive barking | Identify function → teach | 2-6 weeks |
| | alternative behavior | |
+----------------------------+-----------------------------------+-----------------+
| Leash pulling | Penalty yards (stop when | 2-4 weeks |
| | pulling) + reward position | |
+----------------------------+-----------------------------------+-----------------+
→ Specific strategy for behavior.
If err: Severe behavior (bite w/ contact, extreme panic, self-harm) → refer to CAAB or DACVB. This skill covers moderate, not clinical.
Step 3: DS/CC
Core proc for reactivity + fear.
DS/CC Protocol:
1. FIND the threshold: position the dog where the trigger is visible
but the dog is still calm enough to eat treats
2. MARK and TREAT: trigger appears → mark → treat → treat → treat
(classical conditioning: trigger predicts good things)
3. CRITERIA: the dog should be:
- Able to eat treats
- Ears relaxed or neutral (not pinned forward)
- Loose body posture
- Able to look at the trigger and then look back at the handler
4. DECREASE DISTANCE gradually:
Session 1: 50 feet from trigger
Session 3: 45 feet
Session 5: 40 feet
(Only decrease when the dog is consistently relaxed at current distance)
5. SESSION STRUCTURE:
- 5-15 minutes maximum
- 3-5 trigger exposures per session
- End BEFORE the dog goes over threshold
- If the dog goes over threshold, increase distance immediately
and end on a calmer note
6. PROGRESS INDICATORS:
- Dog looks at trigger, then immediately looks at handler ("check-in")
- Dog's threshold distance decreases over sessions
- Recovery time after exposure shortens
- Dog's body language at threshold becomes more relaxed
→ Over wks: threshold shrinks, emotion shifts fear/aggression → neutral/positive.
If err: No progress 3-4 wks of consistent sessions → reassess: (1) below threshold? (2) treats high-value? (3) trigger exposure too frequent outside training (flooding undoes DS/CC)? (4) consult pro.
Step 4: Manage Env
Training changes behavior over time. Mgmt prevents rehearsal now.
Management Strategies:
+----------------------------+------------------------------------------+
| Behavior | Management During Training Period |
+----------------------------+------------------------------------------+
| Dog reactivity | Walk at off-peak hours; cross the street |
| | when another dog approaches; use visual |
| | barriers (parked cars, bushes) |
+----------------------------+------------------------------------------+
| Separation anxiety | Do not leave the dog alone beyond their |
| | current tolerance; use daycare, pet |
| | sitter, or take the dog with you |
+----------------------------+------------------------------------------+
| Resource guarding | Do not approach while eating; trade up |
| | from a distance; manage access to |
| | high-value items |
+----------------------------+------------------------------------------+
| Excessive barking | Block visual triggers (frosted window |
| | film); provide enrichment; address |
| | underlying cause (boredom, anxiety) |
+----------------------------+------------------------------------------+
Every rehearsal of the unwanted behavior strengthens it.
Management prevents rehearsal while training builds the new response.
→ Unwanted behavior not practiced outside controlled sessions.
If err: Mgmt impossible (can't avoid all dog encounters) → reduce training criteria to match reality. Some exposure unavoidable; training sessions need strong enough counter-experience.
Check
- Behavior defined precisely via ABC
- Threshold distance ID'd before DS/CC
- Training consistently below threshold
- Treats high-value enough for dog to eat near trigger
- Sessions 5-15 min, end before over threshold
- Env mgmt prevents rehearsal outside training
- Progress indicators (check-ins, reduced distance) tracked
Traps
- Over threshold: Most common err. Dog can't eat treats → too close. Back up
- Inconsistency: DS/CC needs regular sessions (3-5/wk min). Sporadic → sporadic results
- Flooding: Forcing trigger close up doesn't habituate — traumatizes, worsens behavior
- Punishment: Leash pop, "no" → suppresses warning signals but keeps underlying emotion. Dog learns to bite w/o warning
- Linear progress: Plateaus + regressions normal. Bad session ≠ lost progress. Zoom out, trend over wks
- Ignore medical: Pain, thyroid, neuro → present as behavior. Vet clearance not optional for sudden changes
→
basic-obedience— foundation cmds this builds on; reliable recall essential for safety
GitHub Repository
Related Skills
llamaguard
OtherLlamaGuard is Meta's 7-8B parameter model for moderating LLM inputs and outputs across six safety categories like violence and hate speech. It offers 94-95% accuracy and can be deployed using vLLM, Hugging Face, or Amazon SageMaker. Use this skill to easily integrate content filtering and safety guardrails into your AI applications.
cost-optimization
OtherThis Claude Skill helps developers optimize cloud costs through resource rightsizing, tagging strategies, and spending analysis. It provides a framework for reducing cloud expenses and implementing cost governance across AWS, Azure, and GCP. Use it when you need to analyze infrastructure costs, right-size resources, or meet budget constraints.
quantizing-models-bitsandbytes
OtherThis skill quantizes LLMs to 8-bit or 4-bit precision using bitsandbytes, achieving 50-75% memory reduction with minimal accuracy loss. It's ideal for running larger models on limited GPU memory or accelerating inference, supporting formats like INT8, NF4, and FP4. The skill integrates with HuggingFace Transformers and enables QLoRA training and 8-bit optimizers.
dispatching-parallel-agents
OtherThis Claude Skill dispatches multiple agents to investigate and fix 3+ independent problems concurrently. It is designed for scenarios involving unrelated failures that can be resolved without shared state or dependencies. The core capability is parallel problem-solving, assigning one agent per independent problem domain to maximize efficiency.
