iterative-retrieval
iterative-retrieval is a Context window & token budget skill for AI agents, published by jcarlosrodicio in the opencode-agent-orchestration-kit repository on GitHub. Skillspace rates iterative-retrieval D (64/100) and it passed the safety scan; the rating is based on static analysis only.
Pattern for progressively refining context retrieval to solve the subagent context problem. Use when spawning subagents that need codebase context they cannot predict upfront, or when building multi-agent workflows where context is progressively refined.
- Grade
- D
- Quality
- 64 / 100
- Safety
- Passed
- GitHub stars
- 48
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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