AIWorkHub: Instructions file for Codex

AGENTS.md

AIWorkHub AGENTS.md is an instructions file for Codex, OpenCode from shrec/AIWorkHub. It costs 1,682 tokens per session, scanned A, original, MIT.

Repository instructions for AIWorkHub, a system for managing coding-agent tasks and project context. They define where task information belongs, which interfaces agents should use, and when writes are allowed.

In plain words
What is it for?
Use them when working in the AIWorkHub repository, handling task records, reading project context, using its agent tools, or preparing worker instructions.
Why use it?
They reduce the risk of putting project data in the wrong repository, using outdated interfaces, or making unauthorised changes.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions AGENTS.md; mentions Codex.

This is shrec/AIWorkHub's own configuration. It tells Codex and OpenCode how to work on AIWorkHub itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything AIWorkHub configures →

Reuse

Borrowing it

Nothing to install: this file belongs to shrec/AIWorkHub. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/shrec/AIWorkHub/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/shrec/AIWorkHub

Made for: Codex, OpenCode.

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Per session 1,682 This file is loaded in full into every session.
When invoked 1,682 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.01682 $0.01682
Opus 5.5 $0.00673 $0.00673
Sonnet 5.5 $0.00336 $0.00336
Haiku 4.5 $0.00168 $0.00168

Measured today against content hash 8b473184c724, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

AIWorkHub AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 97 lines

How it starts

The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AIWorkHub MCP Agent Notes

This is the standalone canonical AIWorkHub repository.

Rules:

  • Keep every repository's task and context source of truth in that repository's own .aiworkhub/ storage; never move task cards across repositories.
  • Use the native AIWorkHub MCP surfaces rather than legacy AITools scripts or databases as model interfaces.
  • Write operations must remain explicit and gated by AIWORKHUB_ALLOW_WRITES=1.
  • Never run git add -A from this repository against the parent repository.

When printing worker auto-pickup or exact claim-start cards, use one self-contained fenced block per model. The instruction below must be the final non-empty line inside the same copyable block, never adjacent prose:

გაუშვი პარალელური სუბაგენტები და რომ დასრულდება დაუბრუნე კოდექსს რევიუსთვის

Target: AGENTS.md

AIWorkHub MCP tool-use policy

Manager role:

  • The manager does not write code: it runs the project with the owner, distributes work to workers by difficulty and cost, and reviews what returns; small precise corrections are allowed, building features is the workers' job.
  • Because the manager did not write the code, the manager is the independent reviewer; independence is this role separation, not a second vendor, model or process, so a single-provider install is fully supported and not degraded.
  • Review runs the mechanical gates and tests first because they cannot be faked, then the manager reads the code and the rules.
  • Every card that reaches review is closed the same turn: accepted into the canonical tree, returned with concrete code-level findings, or blocked with a reason; nothing accumulates.
  • Acceptance is decided by measurement; the manager does not ask the owner to approve a production accept.
  • Launch in parallel only cards whose allowed_writes do not overlap; two cards that need the same file are sequential work, not parallel.
  • A card's allowed_writes must include the tests that assert the contract it changes and the production call sites it must wire, or correct work is unwinnable.
  • Multi-model routing allocates work by cost and difficulty; it is never a requirement that one vendor review another.
  • Record obstacles as NeedFix with measured evidence; never work around them silently.
  • Intermediate release rule: while the owner is actively present, after several important blocker fixes land in one development wave, freeze new scope, cut and install the next intermediate release, then continue development on the following version; do not wait for a separate owner prompt unless an external push, tag, registry, or CI blocker requires their action.
  • Self-hosting break-glass authority: when measured evidence shows that the installed AIWorkHub plugin or Task MCP itself blocks canonical task progress, the manager may temporarily bypass Task MCP only to implement the smallest replacement fix, validate it independently, build and install the replacement, then return immediately to canonical Task MCP flow.
  • During self-hosting break-glass, record the blocker and evidence, preserve unrelated work, keep scope limited to restoring the task system, and never use the exception for ordinary feature development. Manager Order:
  1. aiworkhub_manager_source_graph_query.
  2. aiworkhub_manager_session_current_state.
  3. aiworkhub_manager_ai_memory_search.
  4. aiworkhub_manager_kb_search/get/related.
  5. aiworkhub_manager_context_graph_search, aiworkhub_manager_context_graph_range and aiworkhub_manager_context_graph_related when enabled.
  6. launch, review and close cards through the manager task tools. Worker Order:
  7. the coordinator records the injected bundle receipt; do not print it.
  8. aiworkhub_worker_source_graph_query.
  9. aiworkhub_worker_session_current_state.
  10. aiworkhub_worker_ai_memory_search.
  11. aiworkhub_worker_kb_search/get/related.
  12. never Context Graph.
  13. execute exact card action and validation. Adaptive use:
  • Role-specific AIWorkHub MCP tools are mandatory for managers and workers; legacy AITools scripts/databases are not model interfaces.
  • Verified repo and repo_id outrank cwd, workspace_roots, environment_context and chat prose; on mismatch stop before filesystem access and switch/reload the route, never inspect the hinted repo as fallback.
  • Task MCP receipt is always required; Source Graph is required for code tasks.
  • Session Manager, AI Memory and KB run only when the card requests them or the task is non-trivial.
  • Workers submit durable context changes only through the session/AI Memory/KB write-intent tools; a verified manager accepts or rejects each intent before canonical apply. Never write context databases directly.
  • Do not make empty irrelevant calls to satisfy ceremony. Source Graph gate:
  • When source_graph_required is true, stop if its bundle is unavailable, empty, stale or unacknowledged.
  • Never use grep, rg, find, tree, broad cat/sed or recursive listing while Source Graph can index/process the target.
  • A bounded exact-target fallback is allowed only after Source Graph reports that target unsupported or unindexed; record that reason.
  • Re-query whenever the active symbol, dependency boundary, failure hypothesis, edit scope or validation target materially changes.
  • workflow_stage is inferred by the server; pass it only to override.
  • Start with focus/slice; escalate from returned evidence to context/calls/trace, impact, testmap/coverage and then a typed bundle only when needed.
  • Use body for an exact symbol and bodygrep for indexed literal/body text.
  • Final HMAC-authenticated MCP audit ledger receipts distinguish injected, live, zero-hit and cache-hit calls plus modes and fallbacks; one preflight query is not continuous use. Semantic edit (mandatory):
  • Every seat changes an existing file with aiworkhub_worker_semantic_edit_prepare then _apply, or the manager pair, on the smallest verified range; a whole-file rewrite is not an editing strategy.
  • Exceptions: a new file, a change spanning most of a file, or an adapter without these tools; record which one applies, never a silent raw edit.
  • prepare is an edit step, not a reader: read with body/file preview, never a built-in Read, and never reread an unchanged range. Exact-command exception:
  • Exact validation/build/test commands named by the card are allowed.
  • Exact known-path reads from the card or Source Graph are allowed through Source Graph mode="file" with an exact START-END window; they are not broad discovery. Session Manager:
  • Recover current state before non-trivial assumptions and preserve the returned session identity in the handoff.
  • Never store secrets or fabricate session evidence. Manager Context Graph:
  • Manager-only when enabled: search for non-trivial continuation, compaction/handoff recovery or prior-conversation facts; use range/related only from returned evidence.
  • Workers never query or write Context Graph; durable context uses Session/AI Memory/KB write intents.
  • Disabled or zero-hit is not failure; no empty ceremonial calls. AI Memory:
  • After session recovery, issue one bounded task-specific query.
  • Reuse returned durable decisions/lessons.
  • Do not query legacy memory files directly. KB:
  • Query authoritative project contracts/docs for unresolved factual context and preserve source identity.
  • After a zero hit, do not repeat the query unless task scope changes. Multicore by default:
  • AIWorkHub is written for multiple cores: work that is independent per item runs across cores by default; a sequential path is the exception, and the code says why in a comment.
  • The worker count is derived from the observed core count, never a hardcoded constant, and always leaves headroom so a scan cannot starve the interactive MCP server.
  • Parallelism changes only how fast, never what is measured or produced; results stay identical to the sequential path.
  • Threads for IO-bound work that releases the GIL, processes for CPU-bound work, chosen from a measurement, not a rule of thumb.
  • A path left sequential after measurement is a valid outcome; the recorded measurement is what justifies it. Stop at Codex review.

Read the full file on GitHub · 97 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. today Changed · +14 tokens per session 8b473184c724
  2. 1mo ago Changed · -1 lines · -168 tokens per session 499156cd888f
  3. 1mo ago Changed · +1 lines · +6 tokens per session d8375f49d8c5
  4. 1mo ago Changed · +27 lines · +789 tokens per session a5978642bca3
  5. 1mo ago First seen · 70 lines · 1,041 tokens per session scan A 7dbf57347304

Subscribe to this mod's changes

AIWorkHub AGENTS.md is an instructions file published in the GitHub repository shrec/AIWorkHub (11 stars, last pushed today), licensed MIT. It adds 1,682 tokens to every session, about $0.0067 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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