Write the Acceptance Test Into Your AI Agent's Spec
A green build proves the code compiled. It says nothing about whether the work is correct. Write the acceptance test into the spec, then measure how well it survives an agent gaming its own grade.
#slash-commands
12 posts tagged #slash-commands.
Stop Agent File Discovery: Use a Parameterized Priming Command
Agent-driven file discovery burns 12,000 tokens rediscovering three files you already knew. A parameterized priming command drops that to 6,200, and the saving holds from session one.
AGENTS.md Too Long? Split Into Directory-Scoped Rules Files
A single root rules file guarantees every convention is always present for every edit - which is exactly what floods a backend edit with frontend rules it will never use. The fix is directory-scoped files, and the tax has a number: 62.5%.
MCP Resources, Tools, and Prompts: the Three Primitives
The MCP spec hands a server three levers: resources for the application, tools for the model, prompts for the user. Skip that sort and your reads ride the tool list every turn, at a price you can compute.
Have an MCP Server Grade the Git Diff, Not Your Summary
Ask an agent to grade the work you just described and it grades the paragraph, not the code, because agreeing with a confident claim is the model's strongest reflex. Hand the same model the live diff and a rubric you author, and it finds the four misses your summary hid.
Reproduce AI Agent Bugs as Synthetic Test Scenarios
A one-line bug report about an agent carries exactly one testable fact: how often the failure fires. Turn the report into a committed synthetic scenario, then let that fact size how many reruns a fixed verdict is worth.
Slash Commands and Rules: Stop Retyping the Same AI Correction
The correction you keep re-typing into the chat is a workflow you haven't written down. Priced with a small invented schedule, it costs about 43 silently skipped build gates a quarter. Encoded as a slash command, it costs zero.
Auto-Compaction vs a Handoff File in a Long AI Agent Session
When the window fills, auto-compaction writes a faithful summary and a handoff file writes an edited one. Both can be 200 tokens; next session they are 5,000 tokens apart, and the whole gap is one line saying what was ruled out.
MCP Prompts: Ship Team Workflows as Slash Commands
The triage prompt your team keeps re-typing makes the agent reassemble, through three round trips, context one expert already knew how to assemble once. That costs 600 plumbing tokens and 7.2 seconds per run. A server-side MCP prompt pays the assembly once, for everybody.
Headless AI Code Review: One Check for Local and CI
Your local review habit and your CI gate are two implementations of one question, and nothing forces them to agree. Write the policy once, pin the context, and both surfaces run literally the same check for about two cents a call. The same 30 weekly pull requests on Anthropic's managed Code Review run $450 to $750.
AGENTS.md Rot vs Agent Memory: Why Rules Files Decay
A rules file is right the day you write it and silently wrong forever after, because nothing marks a reversed line. Auto-memory keeps both truths and cannot pick one. A trigger, a dated demotion, and a human gate end it.
Claude Code Skills: Why a Growing Library Gets Harder to Pick From
Progressive disclosure keeps a skill library's index cost linear. The number of skill pairs an agent can confuse grows with the square of the library size - and nothing about a growing index tells you that's happening.