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ai-coding-agent-cost

A collection of 11 posts

OpenClaw Finally Counts HTTP API Tokens Where Operators Spend Money

Agent cost dashboards have a simple failure mode: they look useful while quietly ignoring the path where the money is actually spent. OpenClaw PR #96227 fixes one of those failures. OpenAI-compatible HTTP ingress traffic was emitting model-call events, but not model.usage, the event that downstream consumers use for token

Claude Code’s Remote Auto-Compaction Bug Turns Context Management Into Hidden Runtime State

Claude Code’s Remote Auto-Compaction Bug Turns Context Management Into Hidden Runtime State

Context compaction is the garbage collector for coding-agent state. Nobody wants to think about it until it silently stops running. That is why Claude Code issue #70477 is more interesting than a routine token-cost complaint. The report says remote or bridge-attached Claude Code sessions can skip threshold auto-compaction and ignore

Claude Code Dynamic Workflows Need Token Admission Control, Not a Concurrency Dial

Claude Code Dynamic Workflows Need Token Admission Control, Not a Concurrency Dial

Claude Code’s Dynamic Workflows problem is not that users can start too many agents. It is that “too many” is being measured in the wrong unit. A concurrency cap sounds like a control. It is not a budget. Fifteen workers that each grep one small file are cheap. Fifteen

Claude Code Agent Teams Losing Grep and Glob Is a Reminder That Tool Rosters Are Runtime State

An agent that loses Grep and Glob has not just misplaced two convenience tools. It has changed how it thinks, how much it spends, and which safety boundary it reaches for when it needs to inspect a codebase. A fresh Claude Code bug report says enabling CLAUDE_CODE_EXPERIMENTAL_AGENT_

Claude Code’s 98-Agent Research Blowup Is the Cost-Control Story in One Absurd Repro

Claude Code’s 98-Agent Research Blowup Is the Cost-Control Story in One Absurd Repro

“Deep research” sounds responsible until it sends 98 agents to answer a keyboard LED question. Then it sounds like a scheduler without a governor. A new Claude Code enhancement request filed on June 23 reports that the deep-research workflow fanned out into 98 parallel agents for a simple Linux configuration

OpenClaw’s Model-Call Telemetry PR Makes Prompt Cost Debuggable at the Span Where It Happens

OpenClaw’s Model-Call Telemetry PR Makes Prompt Cost Debuggable at the Span Where It Happens

Every agent cost investigation eventually starts with the same miserable question: which part of the prompt got expensive? The invoice says tokens. The trace says a model call happened. The runtime says the agent was “working.” None of that tells you whether the bill came from duplicated system instructions, a

MCP’s write_file Escaping Problem Is Really a Tool-Call Serialization Tax

MCP’s write_file Escaping Problem Is Really a Tool-Call Serialization Tax

Base64 is ugly. Retry loops caused by broken JSON tool calls are uglier. A fresh issue in the Model Context Protocol servers repository proposes adding an optional content_base64 parameter to write_file, plus a matching newText_base64 path for edit operations. The request is narrow: let agents send file

Claude Code 2.1.185 Turns a Retry Message Into a Production-Signal Problem

Claude Code 2.1.185 Turns a Retry Message Into a Production-Signal Problem

Sometimes the smallest changelog item is the one that tells you where the product is hurting. Claude Code 2.1.185 shipped with one public note: the stream-stall message now says “Waiting for API response · will retry in …” instead of “No response from API · Retrying in …”, and the hint appears

Copilot Finally Exposes Per-User AI Credit Burn. Now Teams Can Stop Guessing Which Agent Workflows Are Expensive

Copilot Finally Exposes Per-User AI Credit Burn. Now Teams Can Stop Guessing Which Agent Workflows Are Expensive

Copilot’s credit meter has finally moved from accounting fog to something engineering teams can actually inspect. GitHub added ai_credits_used to the Copilot usage metrics API, giving enterprise administrators and organization owners a per-user view of AI credit consumption across one-day and 28-day user reports. That sounds like