Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/radiantlogicinc/fastworkflow/resolve-parameter-valuesnpx skills add radiantlogicinc/fastworkflow --skill resolve-parameter-valuesgit clone --depth 1 https://github.com/radiantlogicinc/fastworkflowWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00135 | $0.01709 |
| Opus 5 | $0.00068 | $0.00855 |
| Sonnet 5 | $0.00027 | $0.00342 |
| Haiku 4.5 | $0.00014 | $0.00171 |
Grade A, and why
resolve-parameter-values 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 3d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resolving parameter values with db_lookup
A parameter the user types from memory will not match stored data exactly. db_lookup puts a
resolution step between extraction and execution: an exact match passes, a close match is corrected
silently, an ambiguous one comes back as suggestions, and a genuine miss falls through.
Declaring it
class Signature:
class Input(BaseModel):
user_name: str = Field(
description="Name of a person",
examples=['John', 'Jane Doe'],
json_schema_extra={'db_lookup': True},
)
The hook
A static method on the same Signature, dispatching on field name:
from fastworkflow.utils.signatures import DatabaseValidator
@staticmethod
def db_lookup(workflow: fastworkflow.Workflow,
field_name: str,
field_value: str) -> tuple[bool, str | None, list[str]]:
if field_name == 'user_name':
chatroom = workflow.command_context_for_response_generation
key_values = chatroom.list_users()
return DatabaseValidator.fuzzy_match(field_value, key_values)
return (False, '', [])
One hook serves every db_lookup field on the command, so always dispatch on field_name and
always return the neutral (False, '', []) for anything unrecognised.
Fetch the key set at call time from the live context — workflow.command_context_for_response_generation
— never from a module-level constant. The valid set depends on where the user is.
The return contract
(matched, corrected_value, suggestions), and the three outcomes are genuinely different:
| Return | Effect |
|---|---|
(True, value, []) |
the parameter is overwritten with value and validation continues |
(False, None, [s1, s2]) |
the parameter is marked invalid; the caller is asked "Did you mean one of these …?" |
(False, '', []) |
validation passes — absence from the key set is not by itself an error |
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.
- 3d ago First seen · 157 lines · 135 tokens per session scan A d056f4302e4f
resolve-parameter-values is a skill published in the GitHub repository radiantlogicinc/fastworkflow (52 stars, last pushed 6d ago), licensed Apache-2.0. It adds 135 tokens to every session and 1,709 once invoked, about $0.0007 per session on Opus 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 2026-08-30.
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