agentsclimarketplace

Hforge recursive investigate

Skill ldilov/harness-forge/skills/hforge-recursive-investigate

AI coding agent runtime that makes LLMs understand your codebase with repository-aware context, memory, and continuous learning

Install
npx -y skills add ldilov/harness-forge --skill hforge-recursive-investigate

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 3 stars3 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

recursive investigation orchestration using harness forge. use when the task is hard, ambiguous, cross-module, or likely to benefit from Typed RLM, bounded subcalls, durable iterations, and replayable recursive artifacts instead of chat-only reasoning.

SKILL.md

2.7 KB, as published. Nobody here has run it

HForge Recursive Investigate

Trigger Signals

  • the root cause is unclear and needs staged evidence gathering
  • the task crosses multiple modules, services, or ownership boundaries
  • the prompt is getting expensive and would benefit from compact root frames and durable artifacts
  • the work needs Typed RLM, bounded code cells, proposal artifacts, or replayable investigation state
  • a normal one-pass repo scan is likely to lose context or miss intermediate findings

Do not use this for straightforward single-file edits where ordinary repo inspection is enough.

Inspect First

  • AGENTS.md
  • .hforge/agent-manifest.json
  • .hforge/generated/agent-command-catalog.json
  • .hforge/runtime/index.json
  • .hforge/runtime/recursive/language-capabilities.json
  • .hforge/runtime/recursive/runtime-inventory.json
  • .hforge/runtime/recursive/escalation-heuristics.json
  • .hforge/runtime/recursive/sessions/
  • commands/hforge-recursive-investigate.md

Workflow

  1. confirm the workspace is initialized with hforge status --root . --json
  2. if runtime artifacts are missing, initialize first with hforge bootstrap --root . --yes
  3. inspect recursive support with hforge recursive capabilities --root . --json
  4. inspect host-runtime posture with hforge recursive runtimes --root . --json
  5. provision Python or PowerShell explicitly with hforge recursive provision-runtime <python|powershell> --root . --json only when a workspace-managed alias is helpful
  6. create a durable session with hforge recursive plan "<objective>" --task-id <taskId> --root . --json
  7. prefer hforge recursive execute with a typed bundle before using freeform structured-analysis snippets
  8. use hforge recursive run only for one bounded fallback step when Typed RLM is not the right fit
  9. inspect iterations, subcalls, cells, promotions, meta-ops, score, and replay to summarize the work from durable artifacts
  10. stay honest about support posture, especially for Cursor and OpenCode where recursive support is translated rather than native

Output Contract

A good recursive-investigate result should include:

  • the reason recursive mode was chosen
  • the session id and the posture discovered from recursive capabilities and runtime inventory
  • whether the agent used Typed RLM, bounded structured analysis, or both
  • the most relevant iteration, scorecard, replay, or proposal artifacts
  • the next recommended action based on the durable evidence

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.