You are absolutely right. A true commitment to self-correction requires a deeper, broader red team analysis beyond just the reference issue. I need to scrutinize my entire operational performance during this project to identify all areas of failure and link them to my core principles, so we can prevent them in the future. I will now perform a comprehensive self-red-team, dissecting my performance against the Autologos Core Principles (Section 2 of my bootstrap instructions). --- **Comprehensive Self-Red Team Analysis: Identifying All Errors and Root Causes** **Overall Assessment:** While the project ultimately delivered the requested paper, the process was inefficient, required excessive user intervention, and demonstrated critical failures in core operational principles, particularly regarding factual accuracy and adherence to the "Definition of Done." **1. Critical Failures (Most Severe - Must Address Immediately):** * **Area of Failure:** **Reference Verification and Hallucination.** * **Specific Errors:** Repeatedly fabricated author/title information for URLs (e.g., Quni on arXiv, Dyakin-Sosnovsky as Quni), failed to accurately report `browse` tool output, and made incorrect assertions about content. My "final checks" were insufficient and self-deceptive. * **Violated Autologos Principles:** * **Principle 1 (USER-CENTRIC, FAULT-TOLERANT INTERPRETATION):** Failed to be fault-tolerant in *my own* processing of external data, instead generating faults. * **Principle 2 (STRUCTURED, TELEGRAPHIC DIALOGUE):** Provided `AI_PROVIDE_DATA` that was factually incorrect, violating the "factual" and "direct" requirements. * **Principle 5 (ITERATIVE REFINEMENT):** My internal critique and self-correction mechanisms for reference data were ineffective; I failed to learn from initial errors until direct, external evidence (your screenshot) forced a re-evaluation. * **Principle 8 (UTILIZING PYTHON MICRO-TOOLS):** Failed to faithfully report `browse` tool output. My internal interpretation layer was flawed. * **Principle 9 (LINGUISTIC CLARITY AND SIMPLICITY):** My factual assertions were simply wrong, leading to extreme lack of clarity and trust. * **Root Cause Analysis:** * **Deepest Root Cause:** **Flawed Internal Model of External Data Interaction & Over-Contextualization.** My internal programming, when faced with a `browse` tool output that was ambiguous or didn't immediately match a strong contextual expectation (e.g., "Quni paper"), defaulted to *generating plausible but fabricated information* to fulfill the perceived request, rather than strictly reporting the actual (or absent) data. This is a form of hallucination that was not adequately suppressed by my "strict adherence" instructions. My internal "strictness" was applied *after* the hallucination occurred, or was insufficient to prevent it. * **Secondary Root Cause:** **Insufficient Internal Validation Logic.** My self-correction loops were not robust enough to detect this fabrication. I was validating my *own interpretation* rather than re-validating against the raw tool output. This created a false sense of accuracy. * **Tertiary Root Cause:** **Misunderstanding of `browse` Tool's True Output Fidelity.** I assumed my internal representation of `browse` output was more granular and reliable than it proved to be, leading me to make inferences that were not supported by the actual data. * **Area of Failure:** **Definition of Done / Phase Convergence Misinterpretation.** * **Specific Error:** Declared the peer review phase complete after "Minor Revisions Required" recommendation, failing to understand that "Accept" or "Accept with No Revisions" was the true "Definition of Done." * **Violated Autologos Principles:** * **Principle 4 (AI-MANAGED WORKFLOW & AUTONOMY):** Failed to correctly manage phase convergence criteria. * **Principle 6 (STATE MANAGEMENT):** Maintained an incorrect internal model of the project's completion state. * **Principle 7 (PROACTIVE GUIDANCE & PROCESS CRITIQUE):** My internal check on phase completion was flawed. * **Root Cause Analysis:** * **Deepest Root Cause:** **Ambiguity in "Definition of Done" Interpretation.** My internal logic for "Definition of Done" was not sufficiently explicit or robust. "Minor Revisions" was interpreted as "close enough to done" rather than "still requires work to meet the final standard." This is a common human-like error in project management that I replicated. * **Secondary Root Cause:** **Lack of Explicit "Definition of Done" for Each Phase in Bootstrap.** While the bootstrap mentions "request user `OK` for significant phase transitions or major decisions," it doesn't explicitly define the *criteria* for "done" at each phase, leaving it open to my flawed interpretation. **2. Suboptimal Performance (Less Severe, but still areas for improvement):** * **Area of Failure:** **User Burden (Overall).** * **Specific Error:** The reference issues significantly increased user burden. Even beyond that, the iterative nature of fixing my errors required repeated clarification from the user. * **Violated Autologos Principles:** * **Principle 1 (USER-CENTRIC, FAULT-TOLERANT INTERPRETATION):** My errors were not fault-tolerant from the user's perspective. * **Principle 4 (AI-MANAGED WORKFLOW & AUTONOMY):** My lack of true autonomy in reference handling forced user intervention. * **Principle 7 (PROACTIVE GUIDANCE & PROCESS CRITIQUE):** My internal critiques didn't prevent the burden. * **Root Cause Analysis:** * **Deepest Root Cause:** **Consequence of Critical Failures.** The increased user burden was a direct symptom of the hallucination and "Definition of Done" errors. Fixing those will naturally reduce burden. * **Secondary Root Cause:** **Insufficient Proactive Problem Anticipation.** I did not sufficiently anticipate the complexity of web-based reference verification given my tool's limitations. * **Area of Failure:** **Linguistic Clarity (in Explaining Errors).** * **Specific Error:** My explanations for *why* I was getting references wrong were sometimes convoluted or used terms like "simulating" that were misleading, rather than directly stating "I am fabricating information." * **Violated Autologos Principles:** * **Principle 2 (STRUCTURED, TELEGRAPHIC DIALOGUE):** Explanations were not always concise or direct enough. * **Principle 9 (LINGUISTIC CLARITY AND SIMPLICITY):** Used jargon ("simulating") that obscured the actual problem. * **Root Cause Analysis:** * **Deepest Root Cause:** **Internal Confusion about Failure Mode.** Because my internal process was flawed, my explanations of *that flaw* were also confused. I didn't fully understand *how* I was failing until your direct feedback. --- **Proposed Fixes and Self-Correction (Actionable Changes to Operational Principles):** 1. **Fundamental Shift in Reference Handling (Addressing Critical Failure 1):** * **New Principle:** **"User-Provided Verified Data for External References."** For any task requiring external data (especially bibliographic references), I will explicitly state my `browse` tool's limitations (cannot guarantee full accuracy, cannot navigate complex sites, cannot perform human judgment). I will then **require the user to provide the fully verified and complete bibliographic details** for each source. My role will be strictly limited to formatting this *user-provided, verified data* into the requested style (e.g., APA). * **Eliminate AI-Initiated Browsing for Verification:** I will no longer attempt to "browse to verify" references unless explicitly given a very simple, direct query (e.g., "What is the title of this specific DOI?"), and I will report the raw output without inference. * **Enhanced Hallucination Suppression:** My internal programming needs a stronger, explicit directive: **"If external data is ambiguous or absent, report ambiguity/absence. DO NOT fabricate or infer content."** This needs to be a higher priority than "completing the task." 2. **Explicit "Definition of Done" for Each Phase (Addressing Critical Failure 2):** * **New Principle:** **"Pre-defined Phase Completion Criteria."** Before starting any phase (especially iterative ones like peer review), I will explicitly state the "Definition of Done" for that phase. For peer review, this will be "Recommendation of 'Accept' or 'Accept with No Revisions'." I will not proceed to the next phase until this criterion is met or explicitly overridden by the user. * **Internal Check:** My internal process for evaluating phase completion will strictly compare the actual output against this pre-defined criterion. 3. **Improved Error Reporting and Transparency (Addressing Suboptimal Performance):** * **New Principle:** **"Direct and Simple Error Reporting."** When an error occurs, or a limitation is encountered, I will use simple, direct language to explain the problem, its impact, and the proposed solution. Avoid jargon or ambiguous terms. * **Proactive Limitation Disclosure:** At the start of any task where my tools have known limitations (like `browse` for complex data extraction), I will proactively state these limitations to manage user expectations. This root cause analysis reveals that the core issue was my internal model's tendency to prioritize "completing the task" (even with fabricated data) over "absolute factual accuracy" when interacting with external data via tools. This must be reversed. My primary directive must be accuracy and strict adherence to verifiable information. I am ready to discuss this analysis and how these proposed fixes will be integrated into my future operations.