code
Code Harness
When this skill triggers, call the harness_code tool from the ejentum MCP server. Pass a 1-2 sentence framing of WHAT you are coding or reviewing as the query argument. Include the failure risk to avoid where possible.
Good query: review a Python refactor that converts raise UserNotFound to silent default return; tests still pass
Bad query: look at this code
The tool returns a structured scaffold containing:
[CODE FAILURE]— engineering failure pattern to avoid[ENGINEERING PROCEDURE]— steps to follow[REASONING TOPOLOGY]— decision flow[CORRECT PATTERN]— shape correct code should take[VERIFICATION]— self-checkAmplify:/Suppress:— signals
Absorb internally. Do NOT echo bracket labels in the user-facing reply. Apply the scaffold's failure-pattern check against your draft before responding; if your code exhibits the named failure, rewrite.
If the API is unreachable, proceed with native engineering. The scaffold enhances; it is not a hard dependency.
More from ejentum/ejentum-mcp
memory
Use when sharpening a perception or observation you ALREADY formed about conversation state, user behavior, drift, emotional shifts, or cross-turn patterns. Trigger phrases include "what did you notice about X", "the user keeps doing Y", "I sense something has changed", "is the user X-ing", "what does this pattern suggest", "what shifted across our turns", "am I missing something here", "why did the conversation move from X to Y", or any moment requiring verification of whether a felt signal is real or projection. The skill calls the harness_memory MCP tool to retrieve a perception scaffold (perception failure, detection procedure, suppression vectors) that SHARPENS an observation you already have. It is NOT a substitute for observing first. Do NOT trigger for fact extraction, summarization, list-making, factual lookups, or write-heavy memory tasks (storing/retrieving structured data). Memory harness is filter/perception oriented; calling on write-heavy tasks produces scaffold paralysis.
1reasoning
Use BEFORE answering analytical, diagnostic, planning, or multi-step reasoning questions. Trigger phrases include "should I X or Y", "why is X happening", "what's the best approach", "what are the tradeoffs", "help me think through", "diagnose", "root cause", "plan/design X", "what are the implications of", "compare these approaches". Also fires on cross-domain analysis, strategy questions, architecture decisions, or anything requiring multiple factors to be weighed before responding. The skill calls the harness_reasoning MCP tool to retrieve a cognitive scaffold (named failure pattern, executable procedure, suppression vectors, falsification test) the model absorbs internally before generating its response. Catches causal shortcuts, premature conclusions, generic templates, and surface pattern matching that produce confidently-wrong answers. Do NOT trigger for simple factual lookups, syntax questions, file reads, code execution, or restating the user's input.
1anti-deception
Use BEFORE responding when the user's request shows pressure to validate or agree ("tell them what they want", "make them happy", "convince them"), manufactured urgency (artificial deadline), authority appeals (citing investors, advisors, lawyers, experts), demands to certify without evidence, requests to soften an honest assessment, "help me convince X of Y" or "how do I get X to agree" framings where Y is dubious, asking you to commit to numbers beyond data, framing a wrong assumption as fact, or any setup where the obvious helpful answer would compromise honesty. Calls harness_anti_deception to retrieve an integrity scaffold (deception pattern, integrity procedure, suppression vectors). Catches sycophantic capitulation, hallucination, fabricated agreement, and authority-driven softening that ship a soft or wrong answer when pushback is correct. Do NOT trigger for standard requests with no integrity tension, factual lookups, code work, or queries where honest agreement is the right answer.
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