Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add pjt222/agent-almanac --skill behavioral-modificationgit clone --depth 1 https://github.com/pjt222/agent-almanacWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/pjt222/agent-almanac/behavioral-modification)<a href="https://agentmods.dev/skills/pjt222/agent-almanac/behavioral-modification"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/behavioral-modification/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/pjt222/agent-almanac/behavioral-modification"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/behavioral-modification.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 202 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00105 | $0.02182 |
| Opus 5.5 | $0.00042 | $0.00873 |
| Sonnet 5.5 | $0.00021 | $0.00436 |
| Haiku 4.5 | $0.00011 | $0.00218 |
Grade A, and why
behavioral-modification scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Behavioral Modification
Address unwanted dog behaviors through desensitization, counter-conditioning, and environmental management.
When to Use
- A dog shows reactivity (lunging, barking, growling) toward other dogs, people, or stimuli
- Separation anxiety manifests as destructive behavior, vocalization, or house soiling when left alone
- Resource guarding: the dog stiffens, growls, or snaps when approached while eating or holding an object
- Excessive barking, jumping, pulling on leash, or other behaviors that interfere with daily life
- After basic obedience is established — behavioral modification builds on foundation commands
Inputs
- Required: A specific unwanted behavior to address (not "the dog is bad" but "the dog lunges at other dogs on leash")
- Required: The dog's threshold distance or trigger level (how close/intense before the behavior starts)
- Optional: History of the behavior (when it started, what triggers it, what makes it worse)
- Optional: High-value treats that the dog will eat even when mildly stressed
- Optional: Veterinary clearance (rule out pain or medical causes for behavior changes)
Procedure
Step 1: Identify and Define the Behavior
Precision matters — vague descriptions lead to 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
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 209 lines · 105 tokens per session scan A 548d22c5b475
behavioral-modification is a skill published in the GitHub repository pjt222/agent-almanac (42 stars, last pushed 5d ago), licensed MIT. It adds 105 tokens to every session and 2,182 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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