SKILLEMALL.ai

BF context-budget

Plan a session's context window like the budget it is — what loads up front, what gets linked instead, what stays fetch-on-demand, and how to keep the stable prefix cache-friendly so repeated turns cost cents instead of dollars. Use when asked my agent keeps blowing its context, plan what to load into the session, why is every turn so expensive, or design the context for this workflow. Produces the load/link/fetch allocation, the cache-aware prefix layout, the per-turn cost shape, and the eviction rules for when the window fills anyway.

mohitagw15856/pm-claude-skills Agent Skills author: mohitagw15856 MIT 1 file body ≈ 1 293 tokens Open the sourcegithub.com analyzed 2 d ago

Plan a session's context window like the budget it is — what loads up front, what gets linked instead, what stays fetch-on-demand, and how to keep the stable…

As a process F 51/100 · Will not run — References files that are not bundled: ../token-cost/SKILL.md, ../repo-map/SKILL.md, ../context-crusher/SKILL.md

ProcedureAI and agentsFinancetype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
F
51/100
Will not run
References files that are not bundled: ../token-cost/SKILL.md, ../repo-map/SKILL.md, ../context-crusher/SKILL.md
Tools and files w 18
0
Failures and branches w 10
0
When it triggers w 12
20
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: context-budget (mohitagw15856/pm-claude-skills)

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../token-cost/SKILL.md
  • warning missing-ref reference to a missing file: ../repo-map/SKILL.md
  • warning missing-ref reference to a missing file: ../context-crusher/SKILL.md
  • warning missing-ref reference to a missing file: ../token-diet/SKILL.md
  • warning missing-ref reference to a missing file: ../session-handoff/SKILL.md

Process rating: all ten parameters 51/100

Will not run. References files that are not bundled: ../token-cost/SKILL.md, ../repo-map/SKILL.md, ../context-crusher/SKILL.md
  • 0Tools and files. 5 referenced file(s) missing: ../token-cost/SKILL.md, ../repo-map/SKILL.md, ../context-crusher/SKILL.md
  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 23 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1293 tokens
  • 100Progress reporting. Reports progress
  • low 10 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 542: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 23 items
  • +3Output format is stated explicitly

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.