Model Agent Mental States with BDI
Agent decisions become difficult to explain when beliefs, goals, and commitments lack formal structure. This skill models BDI chains with RDF, SPARQL, provenance, and temporal validity.
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "bdi-mental-states" from https://skillstore.io/skills/muratcankoylan-bdi-mental-states.md and its manifest at https://skillstore.io/api/skills/muratcankoylan-bdi-mental-states/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Using "bdi-mental-states". Model an agent that learns an invoice is due and commits to paying it.
Expected outcome:
Using "bdi-mental-states". Explain how to validate a time-sensitive belief model.
Expected outcome:
Check that each belief references a world state, includes justification, has a validity interval, and does not conflict with overlapping beliefs.
Using "bdi-mental-states". Choose between BDI modeling and ordinary persistent memory.
Expected outcome:
Use BDI when the system must explain motivations, commitments, and plans. Use persistent memory when it only needs retained facts.
All 130 static findings are false positives caused by RDF identifiers, Markdown backticks, and BDI terminology. No static item performs network access, command execution, scheduling, or reconnaissance. One medium-risk prompt-injection weakness exists in the documented LAG implementation.
Share the versioned assessment report, neutral badge, embed card, and citations. Skillstore reports evidence without deciding whether this Skill is safe.
https://skillstore.io/skills/muratcankoylan-bdi-mental-states/audits/8?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report[](https://skillstore.io/skills/muratcankoylan-bdi-mental-states?utm_source=security_passport_badge)<a href="https://skillstore.io/skills/muratcankoylan-bdi-mental-states?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/muratcankoylan-bdi-mental-states/security.svg" alt="Skillstore security assessment" loading="lazy"></a><iframe src="https://skillstore.io/embed/skills/muratcankoylan-bdi-mental-states.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>muratcankoylan. (2026). bdi-mental-states security audit report (audit version 8) [Author version unspecified]. Skillstore. https://skillstore.io/skills/muratcankoylan-bdi-mental-states/audits/8@techreport{muratcankoylan-muratcankoylan-bdi-mental-states-2026,
author = {muratcankoylan},
title = {bdi-mental-states security audit report (audit version 8)},
institution = {Skillstore},
year = {2026},
number = {8},
url = {https://skillstore.io/skills/muratcankoylan-bdi-mental-states/audits/8},
note = {Author version unspecified}
}cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "bdi-mental-states security audit report (audit version 8)"
version: "unspecified"
type: report
authors:
- name: "muratcankoylan"
date-released: "2026-08-09"
url: "https://skillstore.io/skills/muratcankoylan-bdi-mental-states/audits/8"
identifiers:
- type: other
value: "skillstore:muratcankoylan-bdi-mental-states:audit:8"
description: "Skillstore immutable audit report identifier"
Define BDI classes and relations that connect perceived world states to explainable decisions.
Create belief-to-desire-to-intention chains with plans, justifications, and validity intervals.
Use competency questions to test provenance, motivation, plan order, and temporal consistency.
Identify the beliefs, desires, intentions, world states, and plans in this scenario: [scenario]. Explain each classification.
Model [scenario] as a grounded belief-to-desire-to-intention chain. Include a plan, justification, and temporal validity for each mental state.
Draft SPARQL competency questions for this BDI model: [model description]. Cover provenance, motivation, plan order, validity, and world-state grounding.
Design a BDI integration for [framework and system]. Specify RDF transformations, validation gates, storage, communication, and prompt-injection controls.
Author
muratcankoylanLicense
MIT
Skillstore revision
r2
Version notice
The author did not declare a version.
Ref
02be9409c79ca1183f7844009c14d9df684d0cf9
Maintenance freshness
8/11/2026
Usage
8 downloads · 487 views
File structure
Compress Long Agent Contexts Reliably
Long agent sessions can lose decisions, file history, and next steps during compression. This skill provides structured methods and probes that preserve operational context.
Build Reliable Agent Evaluations
Agent quality is difficult to measure because outputs vary and may have several valid forms. This skill builds repeatable rubrics, tests, gates, and monitoring.
Diagnose and Repair Context Degradation
Long contexts can hide critical instructions, preserve bad claims, and mix conflicting tasks. This skill diagnoses the failure pattern and recommends placement, filtering, compression, isolation, or recovery strategies.
Optimize AI Context for Cost and Quality
Long AI sessions waste tokens and lose important context. This skill provides measured strategies for budgeting, masking, compaction, caching, retrieval, and partitioning.
Design Reliable Multi-Agent Systems
Multi-agent designs often add cost and coordination failures without improving outcomes. This skill helps select topologies, handoffs, consensus methods, and recovery controls.
Design Reliable Agent Tools
Ambiguous tools cause routing errors, malformed calls, and failed recovery. This skill provides practical patterns for clear schemas, descriptions, responses, and tool catalogs.
Analyze Scientific Data Files
by davila7
Scientific datasets often arrive in specialized formats that are hard to inspect quickly. This skill detects the format, summarizes contents, checks quality, and produces a clear EDA report.
Analyze Single-Cell RNA-Seq with Scanpy
by davila7
Single-cell RNA-seq workflows require careful QC, normalization, clustering, and documentation. This skill gives Scanpy workflows, scripts, templates, and references for reproducible analysis.
Create Publication-Ready Scientific Figures
by davila7
Scientific figures often fail journal checks for size, color, typography, or export format. This skill guides Claude, Codex, and Claude Code through publication-ready plotting workflows.
Process JSON, YAML, and TOML Data
by 0xDarkMatter
Structured configuration data can be hard to inspect across JSON, YAML, and TOML files. This skill guides jq and yq queries for extraction, filtering, conversion, and updates.
Build Therapeutic ML Workflows with PyTDC
by davila7
Therapeutic machine learning requires reliable datasets, meaningful splits, and consistent evaluation. This skill guides PyTDC workflows from dataset selection through molecular optimization.
Draft Nature Data Availability Statements
by Yuan1z0825
Researchers often need precise data availability text, repository plans, and FAIR checks before submission. This skill turns English or Chinese data notes into Nature-style statements, dataset citation actions, and missing-information flags.