Enforce preloaded skill count and SKILL.md line limits per agent tier.
npx skills add https://github.com/monktui/git-review --skill context-budget-monktui
Please help me install this Agent Skill. Skill: context-budget Source: https://github.com/monktui/git-review/tree/main/.claude/skills/context-budget Command: npx skills add https://github.com/monktui/git-review --skill context-budget-monktui
Context budgeting prevents agents from loading too many instructions and tool descriptions, which causes degraded reasoning, repetition, and inconsistent outputs when the prompt becomes too large.
Use context-budget when configuring or spawning an agent by counting preloaded skills and summing their SKILL.md line counts, then trimming to stay under the recommended line limits for that agent tier.
High-intent search queries and answers about installing and using this skill.
You can prevent agent prompt context bloat by enforcing maximum preloaded skill counts and total SKILL.md line limits per session, which keeps prompts focused and prevents degraded reasoning.
Agents ignore instructions or repeat themselves during MCP workflows because the prompt context is too large, causing degraded reasoning that context budgeting solves by enforcing skill preloading limits and MCP overhead accounting.
Set context budgets for Haiku, Sonnet, and Opus tiers by applying per-agent tier thresholds so smaller models stay efficient with lower limits while larger models get more preloaded skill capacity.
Baseline token usage from MCP tool descriptions does affect context budgeting; incorporating MCP overhead accounting into the budget ensures skill limits reflect real runtime context pressure and prevents bloat.
The best way to optimize agent prompts with longer runtimes and inconsistent outputs is using a bloat detection loop that logs measurable signals and per-task outcomes to claude-mem for iterative improvement.
You should not use context budgeting for agent spawning when workflows involve very few preloaded skills or minimal MCP tool descriptions, as the baseline overhead is too low to cause the targeted prompt bloat.
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